software-process-project-managementr17a0539.pdf

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Software Process & Project Management(R17A0539)
Bachelour of arts (Sridevi Women's Engineering College)
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Software Process & Project Management(R17A0539)
Bachelour of arts (Sridevi Women's Engineering College)
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Software Process and Project Management IV YEAR/II SEM MRCET
SOFTWARE PROCESS & PROJECT
MANAGEMENT
[R17A0539]
LECTURE NOTES
B.TECH IV YEAR – II SEM (R17)
(2020-2021)
DEPARTMENT OF
COMPUTER SCIENCE AND ENGINEERING
MALLA REDDY COLLEGE OF ENGINEERING &
TECHNOLOGY
(Autonomous Institution – UGC, Govt. of India)
Recognized under 2(f) and 12 (B) of UGC ACT 1956
(Affiliated to JNTUH, Hyderabad, Approved by AICTE - Accredited by NBA & NAAC 3 8A9 Grade - ISO 9001:2015
Certified)
Maisammaguda, Dhulapally (Post Via. Hakimpet), Secunderabad 3 500100, Telangana State, India
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SYLLABUS
MALLA REDDY COLLEGE OF ENGINEERING AND TECHNOLOGY
IV Year B. Tech CSE -IISem L T/P/DC 4 -/-/- 4
Core Elective 6
(R17A0539)
Software Process & Project Management
OBJECTIVES:
The goals of the course are as follows:
1. To learn the importance of software process maturity & understand related concepts.
2. Understanding the specific roles within a software organization as related to project and process
management
3. Understanding the basic infrastructure competences (e.g., process modeling and measurement)
4. Understanding the basic steps of project planning, project management, quality assurance, and process
management and their relationships.
UNIT I
Software Process Maturity
Software maturity Framework, Principles of Software Process Change, Software Process Assessment, The Initial
Process, The Repeatable Process, The Defined Process, The Managed Process,
TheOptimizingProcess.ProcessReferenceModelsCapabilityMaturityModel(CMM),CMMI, PCMM, PSP,TSP.
UNIT II
Software Project Management Renaissance Conventional Software Management, Evolution of
SoftwareEconomics,ImprovingSoftwareEconomics,Theoldwayandthenewway.Life-Cycle Phases and Process
artifacts Engineering and Production stages, inception phase, elaboration phase, construction phase, transition
phase, artifact sets, management artifacts, engineering artifacts and pragmatic artifacts, model based software
architectures.
UNIT III
Workflows and Checkpoints of process
Software process workflows, Iteration workflows, Major milestones, Minor milestones, Periodic status
assessments.
Process Planning Work break down structures, Planning guidelines, cost and schedule estimating process,
iteration planning process, Pragmatic planning.
UNIT IV
Project Organizations
Line-of- business organizations, project organizations, evolution of organizations, process automation.
Project Control and process instrumentation
The seven core metrics, management indicators, quality indicators, life-cycle expectations, Pragmatic software
metrics, and metrics automation.
UNIT V
CCPDS-R Case Study and Future Software Project Management Practices
Modern Project Profiles, Next-Generation software Economics, Modern Process Transitions.
TEXT BOOKS:
1. ManagingtheSoftwareProcess,WattsS.Humphrey,PearsonEducation.
2. SoftwareProjectManagement,WalkerRoyce,PearsonEducation.
REFERENCE BOOKS:
1. Effective Project Management: Traditional, Agile, Extreme, Robert Wysocki, Sixth edition, Wiley India,rp2011.
2. An Introduction to the Team Software Process, Watts S. Humphrey, Pearson Education,2000
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3. Process Improvement essentials, James R. Persse, O9Reilly,2006
4. Software Project Management, Bob Hughes & Mike Cotterell, fourth edition, TMH,2006
5. Applied Software Project Management, Andrew Stellman & Jennifer Greene, O9Reilly,2006.
6. Head First PMP, Jennifer Greene & Andrew Stellman, O9Reilly,2007
7. Software Engineering Project Management, Richard H. Thayer & Edward Yourdon, 2nd edition, Wiley India,2004.
8. The Art of Project Management, Scott Berkun, SPD, O9Reilly,2011.
9. Applied Software Project Management, Andrew Stellman & Jennifer Greene, SPD, O9Reilly,rp2011.
10. Agile Project Management, Jim Highsmith, Pearson education,2004.
OUTCOMES:
At the end of the course, the student shall be able to:
Apply suitable capability Maturity model for specific scenarios & determine the effectiveness.
Describe and determine the purpose and importance of project management from the perspectives of
planning, tracking and completion ofproject
Compare and differentiate organization structures and projectstructures.
Implement a project to manage project schedule, expenses and resource with the application of
suitable project managementtools
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UNIT I
Software Process Maturity
Software maturity Framework:
Fundamentally, software development must be predictable. The software process is the set of
tools, methods, and practices we use to produce a software product. The objectives of
software process management are to produce products according to plan while
simultaneously improving the organization9s capability to produce better products.
The basic principles are those of statistical process control. A process is said to be stable or
under statistical control if its future performance is predictable within established statistical
limits.When a process is under statistical control, repeating the work in roughly the same way
will produce roughly the same result. To obtain consistently better results, it is necessary to
improve the process. If the process is not under statistical control, sustained progress is not
possible until it is.
Lord Kelvin - <When you can measure what you are speaking about, and express it in
numbers, you know something about it; but when you cannot measure it, when you cannot
express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the
beginning of knowledge, but you have scarcely in your thoughts advanced the stage of
science.= (But, your numbers must be reasonably meaningful.)
The mere act of measuring human processes changes them because of people9s fears, and so
forth. Measurements are both expensive and disruptive; overzealous measurements can
disrupt the process under study.
Principles of Software Process Change:
People:
•The best people are always in short supply
•you probably have about the best team you can get right now.
•With proper leadership and support, most people can do much better than they are currently
doing
Design:
•Superior products have superior design. Successful products are designed by people who
understand the application (domain engineer). •A program should be viewed as executable
knowledge. Program designers should have application knowledge.
The Six Basic Principles of Software Process Change:
•Major changes to the process must start at the top.
•Ultimately, everyone must be involved.
•Effective change requires great knowledge of the current process
•Change is continuous
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•Software process changes will not be retained without conscious effort and periodic
reinforcement
•Software process improvement requires investment
Continuous Change:
•Reactive changes generally make things worse
•Every defect is an improvement opportunity
•Crisis prevention is more important than crisis recovery
Software Processes Changes Won’t Stick by Themselves
The tendency for improvements to deteriorate is characterized by the term entrophy
(Webster9s: a measure of the degree of disorder in a...system; entrophy always increases and
available energy diminishes in a closed system.). New methods must be carefully introduced
and periodically monitored, or they to will rapidly decay. Human adoption of new process
involves four stages:
• Installation - Initial training
• Practice - People learn to perform as instructed
• Proficiency - Traditional learning curve
• Naturalness - Method ingrained and performed without intellectual effort.
It Takes Time, Skill, and Money!
•To improve the software process, someone must work on it
•Unplanned process improvement is wishful thinking
•Automation of a poorly defined process will produce poorly defined results
•Improvements should be made in small steps
•Train!!!!
Some Common Misconceptions about the Software Process
•We must start with firm requirements
•If it passes test it must be OK
•Software quality can9t be measured
•The problems are technical
•We need better people
•Software management is different
Software Process Assessment
Process assessments help software organizations improve themselves by identifying their
crucial problems and establishing improvement priorities. The basic assessment objectives
are:
•Learn how the organization works
•Identify its major problems
•Enroll its opinion leaders in the change process
The essential approach is to conduct a series of structured interviews with key people in the
organization to learn their problems, concerns, and creative ideas.
ASSESSMENT OVERVIEW
A software assessment is not an audit. Audit are conducted for senior managers who suspect
problems and send in experts to uncover them. A software process assessment is a review of
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a software organization to advise its management and professionals on how they can improve
their operation.
The phases of assessment are:
•Preparation - Senior management agrees to participate in the process and to take actions on
the resulting recommendations or explain why not. Concludes with a training program for the
assessment team
•Assessment - The on-site assessment period. It takes several days to two or more weeks. It
concludes with a preliminary report to local management.
•Recommendations - Final recommendations are presented to local managers. A local action
team is then formed to plan and implement the recommendations.
Five Assessment Principles:
•The need for a process model as a basis for assessment
•The requirement for confidentiality
•Senior management involvement
•An attitude of respect for the views of the people in the organization be assessed
•An action orientation
Start with a process model - Without a model, there is no standard; therefore, no measure of
change.
Observe strict confidentiality - Otherwise, people will learn they cannot speak in confidence.
This means managers can9t be in interviews with their subordinates.
Involve senior management - The senior manager (called site manager here) sets the
organizations priorities. The site manager must be personally involved in the assessment and
its follow-up actions. Without this support, the assessment is a waste of time because lasting
improvement must survive periodic crises.
Respect the people in the assessed organization - They probably work hard and are trying to
improve. Do not appear arrogant; otherwise, they will not cooperate and may try to prove the
team is ineffective. The only source of real information is from the workers.
Assessment recommendations should highlight the three or four items of highest priority.
Don9t overwhelm the organization. The report must always be in writing.
Implementation Considerations - The greatest risk is that no significant improvement actions
will be taken (the <disappearing problem= syndrome). Superficial changes won9t help. A
small, full-time group should guide the implementation effort, with participation from other
action plan working groups. Don9t forget that site managers can change or be otherwise
distracted, so don9t rely on that person solely, no matter how committed.
The Initial Process(Level1)
Usually ad hoc and chaotic - Organization operates without formalized procedures, cost
estimates, and project plans. Tools are neither well integrated with the process nor uniformly
applied. Change control is lax, and there is little senior management exposure or
understanding of the problems and issues. Since many problems are deferred or even
forgotten, software installation and maintenance often present serious problems.
While organizations at this level may have formal procedures for planning and tracking work,
there is no management mechanism to insure they are used. Procedures are often abandoned
in a crisis in favor of coding and testing. Level 1 organizations don9t use design and code
inspections and other techniques not directly related to shipping a product.
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Organizations at Level 1 can improve their performance by instituting basic project controls.
The most important ones are
•Project management
•Management oversight
•Quality assurance
•Change control
The Repeatable Process (Level 2)
This level provides control over the way the organization establishes plans and commitments.
This control provides such an improvement over Level 1 that the people in the organization
tend to believe they have mastered the software problem. This strength, however, stems from
their prior experience in doing similar work. Level 2 organizations face major risks when
presented with new challenges.
Some major risks:
•New tools and methods will affect processes, thus destroying the historical base on which
the organization lies. Even with a defined process framework, a new technology can do more
harm than good.
•When the organization must develop a new kind of product, it is entering new territory.
•Major organizational change can be highly disruptive. At Level 2, a new manager has no
orderly basis for understanding an organization9s operation, and new members must learn the
ropes by word of mouth.
Key actions required to advance from Repeatable to the next stage, the Defined Process, are:
•Establish a process group: A process group is a technical resource that focuses heavily on
improving software processes. In most software organizations, all the people are generally
devoted to product work. Until some people are assigned full-time to work on the process,
little orderly progress can be made in improving it.
•Establish a software development process architecture (or development cycle) that describes
the technical and management activities required for proper execution of the development
process. The architecture is a structural decomposition of the development cycle into tasks,
each of which has a defined set of prerequisites, functional decompositions, verification
procedures, and task completion specifications.
•Introduce a family of software engineering methods and technologies. These include design
and code inspections, formal design methods, library control systems, and comprehensive
testing methods. Prototying and modern languages should be considered.
The Defined Process (Level 3)
The organization has the foundation for major and continuing change. When faced with a
crisis, the software teams will continue to use the same process that has been defined.
However, the process is still only qualitative; there is little data to indicate how much is
accomplished or how effective the process is. There is considerable debate about the value of
software process measurements and the best one to use.
The key steps required to advance from the Defined Process to the next level are:
•Establish a minimum set of basic process measurements to identify the quality and cost
parameters of each process step. The objective is to quantify the relative costs and benefits of
each major process activity, such as the cost and yield of error detection and correction
methods.
•Establish a process database and the resources to manage and maintain it. Cost and yield
data should be maintained centrally to guard against loss, to make it available for all projects,
and to facilitate process quality and productivity analysis. Provide sufficient process
resources to gather and maintain the process data and to advise project members on its use.
Assign skilled professionals to monitor the quality of the data before entry into the database
and to provide guidance on the analysis methods and interpretation.
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•Assess the relative quality of each product and inform management where quality targets are
not being met. Should be done by an independent quality assurance group.
The Managed Process (Level 4)
Largest problem at Level 4 is the cost of gathering data. There are many sources of
potentially valuable measure of the software process, but such data are expensive to collect
and maintain.
Productivity data are meaningless unless explicitly defined. For example, the simple measure
of lines of source code per expended development month can vary by 100 times or more,
depending on the interpretation of the parameters
When different groups gather data but do not use identical definitions, the results are not
comparable, even if it makes sense to compare them. It is rare when two processes are
comparable by simple measures. The variations in task complexity caused by different
product types can exceed five to one. Similarly, the cost per line of code for small
modifications is often two to three times that for new programs.
Process data must not be used to compare projects or individuals. Its purpose is too illuminate
the product being developed and to provide an informed basis for improving the process.
When such data are used by management to evaluate individuals or terms, the reliability of
the data itself will deteriorate.
The two fundamental requirements for advancing from the Managed Process to the next level
are:
•Support automatic gathering of process data. All data is subject to error and omission, some
data cannot be gathered by hand, and the accuracy of manually gathered data is often poor.
•Use process data to analyze and to modify the process to prevent problems and improve
efficiency.
The Optimizing Process (Level 5)
To this point software development managers have largely focused on their products and will
typically gather and analyze only data that directly relates to product improvement. In the
Optimizing Process, the data are available to tune the process itself.
For example, many types of errors can be identified far more economically by design or code
inspections than by testing. However, some kinds of errors are either uneconomical to detect
or almost impossible to find except by machine. Examples are errors involving interfaces,
performance, human factors, and error recovery.
So, there are two aspects of testing: removal of defects and assessment of program quality.
To reduce the cost of removing defects, inspections should be emphasized. The role of
functional and system testing should then be changed to one of gathering quality data on the
program. This involves studying each bug to see if it is an isolated problem or if it indicates
design problems that require more comprehensive analysis.
With Level 5, the organization should identify the weakest elements of the process and fix
them. Data are available to justify the application of technology to various critical tasks, and
numerical evidence is available on the effectiveness with which the process has been applied
to any given product.
Process reference models
The process framework or reference model acts as an interface between the way the content
is organized and the way work is performed. A uniform process model organized under a
process reference model makes business modeling and systems designing much easier.
Capability Maturity Model (CMM)
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Broadly refers to a process improvement approach that is based on a process
model. CMM also refers specifically to the first such model, developed by the Software
Engineering Institute (SEI) in the mid-1980s, as well as the family of process models that
followed.
The Software Engineering Institute (SEI) Capability Maturity Model (CMM) specifies an
increasing series of levels of a software development organization. The higher the level, the
better the software development process, hence reaching each level is an expensive and time-
consuming process.
Levels of CMM
 Level One :Initial - The software process is characterized as inconsistent, and
occasionally even chaotic. Defined processes and standard practices that exist are
abandoned during a crisis. Success of the organization majorly depends on an
individual effort, talent, and heroics. The heroes eventually move on to other
organizations taking their wealth of knowledge or lessons learnt with them.
 Level Two: Repeatable - This level of Software Development Organization has a
basic and consistent project management processes to track cost, schedule, and
functionality. The process is in place to repeat the earlier successes on projects with
similar applications. Program management is a key characteristic of a level two
organization.
 Level Three: Defined - The software process for both management and engineering
activities are documented, standardized, and integrated into a standard software
process for the entire organization and all projects across the organization use an
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approved, tailored version of the organization's standard software process for
developing,testing and maintaining the application.
 Level Four: Managed - Management can effectively control the software
development effort using precise measurements. At this level, organization set a
quantitative quality goal for both software process and software maintenance. At this
maturity level, the performance of processes is controlled using statistical and other
quantitative techniques, and is quantitatively predictable.
 Level Five: Optimizing - The Key characteristic of this level is focusing on
continually improving process performance through both incremental and innovative
technological improvements. At this level, changes to the process are to improve the
process performance and at the same time maintaining statistical probability to
achieve the established quantitative process-improvement objectives.
What is CMMI ?
CMM Integration project was formed to sort out the problem of using multiple CMMs.
CMMI Product Team's mission was to combine three Source Models into a single
improvement framework to be used by the organizations pursuing enterprise-wide process
improvement. These three Source Models are :
 Capability Maturity Model for Software (SW-CMM) - v2.0 Draft C
 Electronic Industries Alliance Interim Standard (EIA/IS) - 731 Systems Engineering
 Integrated Product Development Capability Maturity Model (IPD-CMM) v0.98
CMM Integration:
 - builds an initial set of integrated models.
 - improves best practices from source models based on lessons learned.
 - establishes a framework to enable integration of future models.
Following are obvious objectives of CMMI:
 Produce quality products or services: The process-improvement concept in CMMI
models evolved out of the Deming, Juran, and Crosby quality paradigm: Quality
products are a result of quality processes. CMMI has a strong focus on quality-
related activities including requirements management, quality assurance, verification,
and validation.
 Create value for the stockholders: Mature organizations are more likely to make
better cost and revenue estimates than those with less maturity, and then perform in
line with those estimates. CMMI supports quality products, predictable schedules,
and effective measurement to support management in making accurate and
defensible forecasts. This process maturity can guard against project performance
problems that could weaken the value of the organization in the eyes of investors.
 Enhance customer satisfaction: Meeting cost and schedule targets with high-quality
products that are validated against customer needs is a good formula for customer
satisfaction. CMMI addresses all of these ingredients through its emphasis on
planning, monitoring, and measuring, and the improved predictability that comes
with more capable processes.
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The CMM Integration is a model that has integrated several disciplines/bodies of
knowledge. Currently there are four bodies of knowledge available to you when selecting a
CMMI model.
Systems Engineering
Systems engineering covers the development of complete systems, which may or may not
include software. Systems engineers focus on transforming customer needs, expectations,
and constraints into product solutions and supporting these product solutions throughout the
entire lifecycle of the product.
Software Engineering
Software engineering covers the development of software systems. Software engineers focus
on the application of systematic, disciplined, and quantifiable approaches to the
development, operation, and maintenance of software.
Integrated Product and Process Development
Integrated Product and Process Development (IPPD) is a systematic approach that achieves
a timely collaboration of relevant stakeholders throughout the life of the product to better
satisfy customer needs, expectations, and requirements. The processes to support an IPPD
approach are integrated with the other processes in the organization.
If a project or organization chooses IPPD, it performs the IPPD best practices concurrently
with other best practices used to produce products (e.g., those related to systems
engineering). That is, if an organization or project wishes to use IPPD, it must select one or
more disciplines in addition to IPPD.
Supplier Sourcing
As work efforts become more complex, project managers may use suppliers to perform
functions or add modifications to products that are specifically needed by the project. When
those activities are critical, the project benefits from enhanced source analysis and from
monitoring supplier activities before product delivery. Under these circumstances, the
supplier sourcing discipline covers the acquisition of products from suppliers.
Similar to IPPD best practices, supplier sourcing best practices must be selected in
conjunction with best practices used to produce products.
CMMI Discipline Selection
Selecting a discipline may be a difficult step and depends on what an organization wants to
improve.
 If you are improving your systems engineering processes, like Configuration
Management, Measurement and Analysis, Organizational Process Focus, Project
Monitoring and Control, Process and Product Quality Assurance, Risk Management,
Supplier Agreement Management etc., then you should select Systems engineering
(SE) discipline. The discipline amplifications for systems engineering receive special
emphasis.
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 If you are improving your integrated product and process development processes like
Integrated Teaming, Organizational Environment for Integration, then you should
select IPPD. The discipline amplifications for IPPD receive special emphasis.
 If you are improving your source selection processes like Integrated Supplier
Management then you should select Supplier sourcing (SS). The discipline
amplifications for supplier sourcing receive special emphasis.
 If you are improving multiple disciplines, then you need to work on all the areas
related to those disciplines and pay attention to all of the discipline amplifications for
those disciplines.
The CMMI is structured as follows −
 Maturity Levels (staged representation) or Capability Levels (continuous
representation)
 Process Areas
 Goals: Generic and Specific
 Common Features
 Practices: Generic and Specific
This chapter will discuss about two CMMI representations and rest of the subjects will be
covered in subsequent chapters.
A representation allows an organization to pursue different improvement objectives. An
organization can go for one of the following two improvement paths.
Staged Representation
The staged representation is the approach used in the Software CMM. It is an approach that
uses predefined sets of process areas to define an improvement path for an organization.
This improvement path is described by a model component called a Maturity Level. A
maturity level is a well-defined evolutionary plateau towards achieving improved
organizational processes.
CMMI Staged Representation
 Provides a proven sequence of improvements, each serving as a foundation for the
next.
 Permits comparisons across and among organizations by the use of maturity levels.
 Provides an easy migration from the SW-CMM to CMMI.
 Provides a single rating that summarizes appraisal results and allows comparisons
among organizations.
Thus Staged Representation provides a pre-defined roadmap for organizational improvement
based on proven grouping and ordering of processes and associated organizational
relationships. You cannot divert from the sequence of steps.
CMMI Staged Structure
Following picture illustrates CMMI Staged Model Structure.
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Continuous Representation
Continuous representation is the approach used in the SECM and the IPD-CMM. This
approach allows an organization to select a specific process area and make improvements
based on it. The continuous representation uses Capability Levels to characterize
improvement relative to an individual process area.
CMMI Continuous Representation
 Allows you to select the order of improvement that best meets your organization's
business objectives and mitigates your organization's areas of risk.
 Enables comparisons across and among organizations on a process-area-by-process-
area basis.
 Provides an easy migration from EIA 731 (and other models with a continuous
representation) to CMMI.
Thus Continuous Representation provides flexibility to organizations to choose the
processes for improvement, as well as the amount of improvement required.
CMMI Continuous Structure
The following picture illustrates the CMMI Continuous Model Structure.
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Continuous vs Staged Representations
Continuous Representation Staged Representation
Process areas are organized by
process area categories.
Process areas are organized by maturity levels.
Improvement is measured using
capability levels. Capability levels
measure the maturity of a particular
process across an organization; it
ranges from 0 through 5.
Improvement is measured using maturity levels. Maturity
levels measure the maturity of a set of processes across an
organization: it ranges from 1 through 5.
There are two types of specific
practices: base and advanced. All
specific practices appear in the
continuous representation.
There is only one type of specific practice. The concepts of
base and advanced practices are not used. All specific
practices appear in the staged representation except when a
related base-advanced pair of practices appears in the
continuous representation, in which case only the advanced
practice appears in the staged representation.
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Capability levels are used to
organize the generic practices.
Common features are used to organize generic practices.
All generic practices are included in
each process area.
Only the level 2 and level 3 generic practices are included.
Equivalent staging allows
determination of a maturity level
from an organization's achievement
profile.
There is no need for an equivalence mechanism to back the
continuous representation because each organization can
choose what to improve and how much to improve using the
staged representation.
 Increase market share: Market share is a result of many factors, including quality
products and services, name identification, pricing, and image. Customers like to
deal with suppliers who have a reputation for meeting their commitments.
 Gain an industry-wide recognition for excellence: The best way to develop a
reputation for excellence is to consistently perform well on projects, delivering
quality products and services within cost and schedule parameters. Having processes
that conform to CMMI requirements can enhance that reputation.
A maturity level is a well-defined evolutionary plateau toward achieving a mature software
process. Each maturity level provides a layer in the foundation for continuous process
improvement.
CMMI models with staged representation, have five maturity levels designated by the
numbers 1 through 5. They are −
 Initial
 Managed
 Defined
 Quantitatively Managed
 Optimizing
CMMI Staged Representation Maturity Levels
The following image shows the maturity levels in a CMMI staged representation.
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Now we will learn the details about each maturity level. Next section will list down all the
process areas related to these maturity levels.
Maturity Level Details
Maturity levels consist of a predefined set of process areas. The maturity levels are
measured by the achievement of the specific and generic goals that apply to each predefined
set of process areas. The following sections describe the characteristics of each maturity
level in detail.
Maturity Level 1 Initial
At maturity level 1, processes are usually ad hoc and chaotic. The organization usually does
not provide a stable environment. Success in these organizations depend on the competence
and heroics of the people in the organization and not on the use of proven processes.
Maturity level 1 organizations often produce products and services that work; however, they
frequently exceed the budget and schedule of their projects.
Maturity level 1 organizations are characterized by a tendency to over commit, abandon
processes in the time of crisis, and not be able to repeat their past successes.
Maturity Level 2 Managed
At maturity level 2, an organization has achieved all the specific and generic goals of the
maturity level 2 process areas. In other words, the projects of the organization have ensured
that requirements are managed and that processes are planned, performed, measured, and
controlled.
The process discipline reflected by maturity level 2 helps to ensure that existing practices are
retained during times of stress. When these practices are in place, projects are performed and
managed according to their documented plans.
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At maturity level 2, requirements, processes, work products, and services are managed. The
status of the work products and the delivery of services are visible to management at defined
points.
Commitments are established among relevant stakeholders and are revised as needed. Work
products are reviewed with stakeholders and are controlled.
The work products and services satisfy their specified requirements, standards, and
objectives.
Maturity Level 3 Defined
At maturity level 3, an organization has achieved all the specific and generic goals of the
process areas assigned to maturity levels 2 and 3.
At maturity level 3, processes are well characterized and understood, and are described in
standards, procedures, tools, and methods.
A critical distinction between maturity level 2 and maturity level 3 is the scope of standards,
process descriptions, and procedures. At maturity level 2, the standards, process
descriptions, and procedures may be quite different in each specific instance of the process
(for example, on a particular project).
At maturity level 3, the standards, process descriptions, and procedures for a project are
tailored from the organization's set of standard processes to suit a particular project or
organizational unit. The organization's set of standard processes includes the processes
addressed at maturity level 2 and maturity level 3. As a result, the processes that are
performed across the organization are consistent except for the differences allowed by the
tailoring guidelines.
Another critical distinction is that at maturity level 3, processes are typically described in
more detail and more rigorously than at maturity level 2. At maturity level 3, processes are
managed more proactively using an understanding of the interrelationships of the process
activities and detailed measures of the process, its work products, and its services.
Maturity Level 4 Quantitatively Managed
At maturity level 4, an organization has achieved all the specific goals of the process areas
assigned to maturity levels 2, 3, and 4 and the generic goals assigned to maturity levels 2
and 3.
At maturity level 4, sub-processes are selected that significantly contribute to the overall
process performance. These selected sub-processes are controlled using statistical and other
quantitative techniques.
Quantitative objectives for quality and process performance are established and used as
criteria in managing the processes. Quantitative objectives are based on the needs of the
customer, end users, organization, and process implementers. Quality and process
performance are understood in statistical terms and are managed throughout the life of the
processes.
For these processes, detailed measures of process performance are collected and statistically
analyzed. Special causes of process variation are identified and, where appropriate, the
sources of special causes are corrected to prevent future occurrences.
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Quality and process performance measures are incorporated into the organization's
measurement repository to support fact-based decision making in the future.
A critical distinction between maturity level 3 and maturity level 4 is the predictability of
process performance. At maturity level 4, the performance of processes is controlled using
statistical and other quantitative techniques, and is quantitatively predictable. At maturity
level 3, processes are only qualitatively predictable.
Maturity Level 5 Optimizing
At maturity level 5, an organization has achieved all the specific goalsof the process areas
assigned to maturity levels 2, 3, 4, and 5 and the generic goals assigned to maturity levels 2
and 3.
Processes are continually improved based on a quantitative understanding of the common
causes of variation inherent in processes.
This level focuses on continually improving process performance through both incremental
and innovative technological improvements.
The quantitative process-improvement objectives for the organization are established,
continually revised to reflect changing business objectives, and used as criteria in managing
process improvement.
The effects of deployed process improvements are measured and evaluated against the
quantitative process-improvement objectives. Both the defined processes and the
organization's set of standard processes are targets of measurable improvement activities.
Optimizing processes that are agile and innovative, depends on the participation of an
empowered workforce aligned with the business values and objectives of the organization.
The organization's ability to rapidly respond to changes and opportunities is enhanced by
finding ways to accelerate and share learning. Improvement of the processes is inherently a
role that everybody has to play, resulting in a cycle of continual improvement.
A critical distinction between maturity level 4 and maturity level 5 is the type of process
variation addressed. At maturity level 4, processes are concerned with addressing special
causes of process variation and providing statistical predictability of the results. Though
processes may produce predictable results, the results may be insufficient to achieve the
established objectives. At maturity level 5, processes are concerned with addressing
common causes of process variation and changing the process (that is, shifting the means of
the process performance) to improve process performance (while maintaining statistical
predictability) to achieve the established quantitative process-improvement objectives.
Maturity Levels Should Not be Skipped
Each maturity level provides a necessary foundation for effective implementation of
processes at the next level.
 Higher level processes have less chance of success without the discipline provided by
lower levels.
 The effect of innovation can be obscured in a noisy process.
Higher maturity level processes may be performed by organizations at lower maturity levels,
with the risk of not being consistently applied in a crisis.
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Maturity Levels and Process Areas
Here is a list of all the corresponding process areas defined for a software organization.
These process areas may be different for different organization.
Level Focus Key Process Area Result
5
Optimizing
Continuous Process
Improvement
Organizational Innovation and
Deployment
Causal Analysis and Resolution
Highest
Quality
/
Lowest
Risk
4
Quantitatively
Managed
Quantitatively Managed
Organizational Process Performance
Quantitative Project Management
Higher
Quality
/ Lower
Risk
3
Defined
Process Standardization
Requirements Development
Technical Solution
Product Integration
Verification
Validation
Organizational Process Focus
Organizational Process Definition
Organizational Training
Integrated Project Mgmt (with IPPD
extras)
Risk Management
Decision Analysis and Resolution
Integrated Teaming (IPPD only)
Org. Environment for Integration
(IPPD only)
Integrated Supplier Management (SS
Medium
Quality
/
Medium
Risk
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only)
2
Managed
Basic Project Management
Requirements Management
Project Planning
Project Monitoring and Control
Supplier Agreement Management
Measurement and Analysis
Process and Product Quality Assurance
Configuration Management
Low
Quality
/ High
Risk
1
Initial
Process is informal and
Adhoc
Lowest
Quality
/
Highest
Risk
A capability level is a well-defined evolutionary plateau describing the organization's
capability relative to a process area. A capability level consists of related specific and
generic practices for a process area that can improve the organization's processes associated
with that process area. Each level is a layer in the foundation for continuous process
improvement.
Thus, capability levels are cumulative, i.e., a higher capability level includes the attributes of
the lower levels.
In CMMI models with a continuous representation, there are six capability levels designated
by the numbers 0 through 5.
 0 − Incomplete
 1 − Performed
 2 − Managed
 3 − Defined
 4 − Quantitatively Managed
 5 − Optimizing
A short description of each capability level is as follows −
Capability Level 0: Incomplete
An "incomplete process" is a process that is either not performed or partially performed.
One or more of the specific goals of the process area are not satisfied and no generic goals
exist for this level since there is no reason to institutionalize a partially performed process.
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This is tantamount to Maturity Level 1 in the staged representation.
Capability Level 1: Performed
A Capability Level 1 process is a process that is expected to perform all of the Capability
Level 1 specific and generic practices. Performance may not be stable and may not meet
specific objectives such as quality, cost, and schedule, but useful work can be done. This is
only a start, or baby-step, in process improvement. It means that you are doing something
but you cannot prove that it is really working for you.
Capability Level 2: Managed
A managed process is planned, performed, monitored, and controlled for individual projects,
groups, or stand-alone processes to achieve a given purpose. Managing the process achieves
both the model objectives for the process as well as other objectives, such as cost, schedule,
and quality. As the title of this level indicates, you are actively managing the way things are
done in your organization. You have some metrics that are consistently collected and applied
to your management approach.
Note − metrics are collected and used at all levels of the CMMI, in both the staged and
continuous representations. It is a bitter fallacy to think that an organization can wait until
Capability Level 4 to use the metrics.
Capability Level 3: Defined
A capability level 3 process is characterized as a "defined process." A defined process is a
managed (capability level 2) process that is tailored from the organization's set of standard
processes according to the organization's tailoring guidelines, and contributes work
products, measures, and other process-improvement information to the organizational
process assets.
Capability Level 4: Quantitatively Managed
A capability level 4 process is characterized as a "quantitatively managed process." A
quantitatively managed process is a defined (capability level 3) process that is controlled
using statistical and other quantitative techniques. Quantitative objectives for quality and
process performance are established and used as criteria in managing the process. Quality
and process performance is understood in statistical terms and is managed throughout the
life of the process.
Capability Level 5: Optimizing
An optimizing process is a quantitatively managed process that is improved, based on an
understanding of the common causes of process variation inherent to the process. It focuses
on continually improving process performance through both incremental and innovative
improvements. Both the defined processes and the organization's set of standard processes
are the targets of improvement activities.
Capability Level 4 focuses on establishing baselines, models, and measurements for process
performance. Capability Level 5 focuses on studying performance results across the
organization or entire enterprise, finding common causes of problems in how the work is
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done (the process[es] used), and fixing the problems in the process. The fix would include
updating the process documentation and training involved where the errors were injected.
Organization of Process Areas in Continuous Representation
Category Process Area
Project Management  Project Planning
 Project Monitoring and Control
 Supplier Agreement Management
 Integrated Project Management(IPPD)
 Integrated Supplier Management (SS)
 Integrated Teaming (IPPD)
 Risk Management Quantitative Project Management
Support  Configuration Management
 Process and Product Quality Assurance
 Measurement and Analysis Causal Analysis and Resolution
 Decision Analysis and Resolution
 Organizational Environment for Integration (IPPD)
Engineering  Requirements Management
 Requirements Development
 Technical Solution
 Product Integration
 Verification
 Validation
Process Management  Organizational Process Focus
 Organizational Process Definition
 Organizational Training
 Organizational Process Performance
 Organizational Innovation and Deployment
PCMM: 
The People Capability Maturity Model (People CMM, P-CMM) is part of the CMMI product
family of process maturity models. It is a framework to guide organisations in improving
their processes for managing and developing human workforces. It helps organisations to
characterize the maturity of their workforce practices, establish a program of continuous
workforce development, set priorities for improvement actions, integrate workforce
development with Process Improvement, and establish a culture of excellence. PCMM is
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based on proven practices in fields of human resources, knowledge management, and
organisational development.
P-CMM is part of the CMMI product family of process maturity models. It describes a
progression for continuous improvement and process improvement of the HR processes for
managing and developing human workforces.
The P-CMM framework enables organisations to incrementally focus on key process
areas and to lay foundations for improvement in workforce practices. Unlike other HR
models, P-CMM requires that key process areas, improvements, interventions, policies, and
procedures are institutionalised across the organisation 4 irrespective of function or level.
Therefore, all improvements have to percolate throughout the organisation, to ensure
consistency of focus, to place emphasis on a participatory culture, embodied in a team-based
environment, and encouraging individual innovation and creativity.
Process Maturity Rating
The process maturity rating is from ad hoc and inconsistently performed practices, to a
mature and disciplined development of the knowledge, skills, and motivation of the
workforce.
Traditionally, process maturity models like ISO/IEC 15504 or CMMI focus on organisational
improvement with respect to operational (Product) Development Processes. PCMM in
contrast focus instead on the three prominent factors for operational capability to deliver
successful products and services:
1. People
2. Process
3. Products, Technology
Thus, these 3Ps of PCMM are comparable to ITIL's 4Ps: People, Processes, Products (tools
and technology) and Partners (suppliers, vendors, and outsourcing organisations). P-CMM is
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characterised by a holistic approach to people-related issues. Instead of looking at traditional
Human Resource interventions in a reactionary scrappy fashion. The P-CMM framework
enables organisations to incrementally focus on key process areas and to lay foundations for
improvement in workforce practices.
Unlike other HR models, P-CMM requires that key process areas, improvements,
interventions, policies, and procedures are institutionalized across the organisation 4
irrespective of function or level. Therefore, all improvements have to percolate throughout
the organisation, to ensure consistency of focus, to place emphasis on a participatory culture,
embodied in a team-based environment, and encouraging individual innovation and
creativity.
P-CMM Maturity Levels
Like other staged maturity models of the CMMI product family developed at the Software
Engineering Institute (SEI) at Carnegie-Mellon University, the P-CMM consists of maturity
levels that establish successive foundations for continuously improving workforce
competencies.
These range from initial (Level 1), where workforce practices are performed inconsistently or
ritualistically and frequently fail to achieve their intended purpose, to the optimised level
(Level 5), where everyone in the organisation is focused on continuously improving their
Capability and the organisation's workforce practices.
The five maturity levels of the People CMM are:
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1. Initial.
2. Repeatable. The key process areas at Level 2 focus on instilling basic discipline into
workforce activities. They are:
o Work Environment
o Communications
o Staffing
o Performance Management
o Training
o Compensation
3. Defined. The key process areas at Level 3 address issues surrounding the
identification of the organisation's primary competencies and aligning its people
management activities with them. They are:
o Knowledge and Skills Analysis
o Workforce Planning
o Competency Development
o Career Development
o Competency-Based Practices
o Participatory Culture
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4. Managed. The key process areas at Level 4 focus on quantitatively managing
organisational growth in people management capabilities and in establishing
competency-based teams. They are:
o Mentoring
o Team Building
o Team-Based Practices
o Organisational Competency Management
o Organisational
o Performance Alignment
5. Optimising. The key process areas at Level 5 cover the issues that address continuous
improvement of methods for developing competency, at both the organisational and
the individual level. They are:
o Personal Competency Development
o Coaching
o Continuous Workforce Innovation
PSP
The Personal Software Process (PSP) is a structured software development process that is
designed to help software engineers better understand and improve their performance by
bringing discipline to the way they develop software and tracking their predicted and actual
development of the code. It clearly shows developers how to manage the quality of their
products, how to make a sound plan, and how to make commitments. It also offers them the
data to justify their plans. They can evaluate their work and suggest improvement direction
by analyzing and reviewing development time, defects, and size data. The PSP was created
by Watts Humphrey to apply the underlying principles of the Software Engineering Institute's
(SEI) Capability Maturity Model (CMM) to the software development practices of a single
developer. It claims to give software engineers the process skills necessary to work on a team
software process (TSP) team.
The PSP aims to provide software engineers with disciplined methods for improving personal
software development processes. The PSP helps software engineers to:
 Improve their estimating and planning skills.
 Make commitments they can keep.
 Manage the quality of their projects.
 Reduce the number of defects in their work.
 PSP training follows an evolutionary improvement approach: an engineer learning to
integrate the PSP into his or her process begins at the first level 3 PSP0 3 and
progresses in process maturity to the final level 3 PSP2.1. Each Level has detailed
scripts, checklists and templates to guide the engineer through required steps and
helps the engineer improve their own personal software process. Humphrey
encourages proficient engineers to customize these scripts and templates as they gain
an understanding of their own strengths and weaknesses.
 Process
The input to PSP is the requirements; requirements document is completed and
delivered to the engineer.
 PSP0, PSP0.1 (Introduces process discipline and measurement)
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 PSP0 has 3 phases: planning, development (design, code, compile, test) and a post
mortem. A baseline is established of current process measuring: time spent on
programming, faults injected/removed, size of a program. In a post mortem, the
engineer ensures all data for the projects has been properly recorded and analysed.
PSP0.1 advances the process by adding a coding standard, a size measurement and the
development of a personal process improvement plan (PIP). In the PIP, the engineer
records ideas for improving his own process.
 PSP1, PSP1.1 (Introduces estimating and planning)
 Based upon the baseline data collected in PSP0 and PSP0.1, the engineer estimates
how large a new program will be and prepares a test report (PSP1). Accumulated data
from previous projects is used to estimate the total time. Each new project will record
the actual time spent. This information is used for task and schedule planning and
estimation (PSP1.1).
 PSP2, PSP2.1 (Introduces quality management and design)
 PSP2 adds two new phases: design review and code review. Defect prevention and
removal of them are the focus at the PSP2. Engineers learn to evaluate and improve
their process by measuring how long tasks take and the number of defects they inject
and remove in each phase of development. Engineers construct and use checklists for
design and code reviews. PSP2.1 introduces design specification and analysis
techniques
 (PSP3 is a legacy level that has been superseded by TSP.)
One of the core aspects of the PSP is using historical data to analyze and improve process
performance. PSP data collection is supported by four main elements:
 Scripts
 Measures
 Standards
 Forms
The PSP scripts provide expert-level guidance to following the process steps and they
provide a framework for applying the PSP measures. The PSP has four core measures:
 Size 3 the size measure for a product part, such as lines of code (LOC).
 Effort 3 the time required to complete a task, usually recorded in minutes.
 Quality 3 the number of defects in the product.
 Schedule 3 a measure of project progression, tracked against planned and actual
completion dates.
Applying standards to the process can ensure the data is precise and consistent. Data is
logged in forms, normally using a PSP software tool. The SEI has developed a PSP tool and
there are also open source options available, such as Process Dashboard.
The key data collected in the PSP tool are time, defect, and size data 3 the time spent in each
phase; when and where defects were injected, found, and fixed; and the size of the product
parts. Software developers use many other measures that are derived from these three basic
measures to understand and improve their performance. Derived measures include:
 estimation accuracy (size/time)
 prediction intervals (size/time)
 time in phase distribution
 defect injection distribution
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 defect removal distribution
 productivity
 reuse percentage
 cost performance index
 planned value
 earned value
 predicted earned value
 defect density
 defect density by phase
 defect removal rate by phase
 defect removal leverage
 review rates
 process yield
 phase yield
 failure cost of quality (COQ)
 appraisal COQ
 appraisal/failure COQ ratio
Planning and tracking
Logging time, defect, and size data is an essential part of planning and tracking PSP projects,
as historical data is used to improve estimating accuracy.
The PSP uses the PROxy-Based Estimation (PROBE) method to improve a developer's
estimating skills for more accurate project planning. For project tracking, the PSP uses
the earned value method.
The PSP also uses statistical techniques, such as correlation, linear regression, and standard
deviation, to translate data into useful information for improving estimating, planning and
quality. These statistical formulas are calculated by the PSP tool.
Using the PSP
The PSP is intended to help a developer improve their personal process; therefore PSP
developers are expected to continue adapting the process to ensure it meets their personal
needs.
PSP and the TSP
In practice, PSP skills are used in a TSP team environment. TSP teams consist of PSP-trained
developers who volunteer for areas of project responsibility, so the project is managed by the
team itself. Using personal data gathered using their PSP skills; the team makes the plans, the
estimates, and controls the quality.
Using PSP process methods can help TSP teams to meet their schedule commitments and
produce high quality software. For example, according to research by Watts Humphrey, a
third of all software projects fail,[3]
but an SEI study on 20 TSP projects in 13 different
organizations found that TSP teams missed their target schedules by an average of only six
percent.[4]
Successfully meeting schedule commitments can be attributed to using historical data to
make more accurate estimates, so projects are based on realistic plans 3 and by using PSP
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quality methods, they produce low-defect software, which reduces time spent on removing
defects in later phases, such as integration and acceptance testing.
PSP and other methodologies[edit]
The PSP is a personal process that can be adapted to suit the needs of the individual
developer. It is not specific to any programming or design methodology; therefore it can be
used with different methodologies, including Agile software development.
Software engineering methods can be considered to vary from predictive through adaptive.
The PSP is a predictive methodology, and Agile is considered adaptive, but despite their
differences, the TSP/PSP and Agile share several concepts and approaches 3 particularly in
regard to team organization. They both enable the team to:
 Define their goals and standards.
 Estimate and schedule the work.
 Determine realistic and attainable schedules.
 Make plans and process improvements.
Both Agile and the TSP/PSP share the idea of team members taking responsibility for their
own work and working together to agree on a realistic plan, creating an environment of trust
and accountability. However, the TSP/PSP differs from Agile in its emphasis on documenting
the process and its use of data for predicting and defining project schedules.
Quality[edit]
High-quality software is the goal of the PSP, and quality is measured in terms of defects. For
the PSP, a quality process should produce low-defect software that meets the user needs.
The PSP phase structure enables PSP developers to catch defects early. By catching defects
early, the PSP can reduce the amount of time spent in later phases, such as Test.
The PSP theory is that it is more economical and effective to remove defects as close as
possible to where and when they were injected, so software engineers are encouraged to
conduct personal reviews for each phase of development. Therefore, the PSP phase structure
includes two review phases:
 Design Review
 Code Review
To do an effective review, you need to follow a structured review process. The PSP
recommends using checklists to help developers to consistently follow an orderly procedure.
The PSP follows the premise that when people make mistakes, their errors are usually
predictable, so PSP developers can personalize their checklists to target their own common
errors. Software engineers are also expected to complete process improvement proposals, to
identify areas of weakness in their current performance that they should target for
improvement. Historical project data, which exposes where time is spent and defects
introduced, help developers to identify areas to improve.
PSP developers are also expected to conduct personal reviews before their work undergoes a
peer or team review.
TSP
The team software process (TSP) provides a defined operational process framework that is
designed to help teams of managers and engineers organize projects and produce software the
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principles products that range in size from small projects of several thousand lines of code
(KLOC) to very large projects greater than half a million lines of code. The TSP is intended
to improve the levels of quality and productivity of a team's software development project, in
order to help them better meet the cost and schedule commitments of developing a software
system
The initial version of the TSP was developed and piloted by Watts Humphrey in the late
1990s and the Technical Report for TSP sponsored by the U.S. Department of Defense was
published in November 2000. The book by Watts Humphrey, Introduction to the Team
Software Process, presents a view of the TSP intended for use in academic settings, that
focuses on the process of building a software production team, establishing team goals,
distributing team roles, and other teamwork-related activities.
The primary goal of TSP is to create a team environment for establishing and maintaining a
self-directed team, and supporting disciplined individual work as a base of PSP framework.
Self-directed team means that the team manages itself, plans and tracks their work, manages
the quality of their work, and works proactively to meet team goals. TSP has two principal
components: team-building and team-working. Team-building is a process that defines roles
for each team member and sets up teamwork through TSP launch and periodical relaunch.
Team-working is a process that deals with engineering processes and practices utilized by the
team. TSP, in short, provides engineers and managers with a way that establishes and
manages their team to produce the high-quality software on schedule and budget.
How TSP works
Before engineers can participate in the TSP, it is required that they have already learned
about the PSP, so that the TSP can work effectively. Training is also required for other team
members, the team lead and management. The TSP software development cycle begins with
a planning process called the launch, led by a coach who has been specially trained, and is
either certified or provisional. The launch is designed to begin the team building process, and
during this time teams and managers establish goals, define team roles, assess risks, estimate
effort, allocate tasks, and produce a team plan. During an execution phase, developers track
planned and actual effort, schedule, and defects meeting regularly (usually weekly) to report
status and revise plans. A development cycle ends with a Post Mortem to assess performance,
revise planning parameters, and capture lessons learned for process improvement.
The coach role focuses on supporting the team and the individuals on the team as the process
expert while being independent of direct project management responsibility. The team leader
role is different from the coach role in that, team leaders are responsible to management for
products and project outcomes while the coach is responsible for developing individual and
team performance.
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UNIT 2
Software Project Management Renaissance
Conventional Software Management :
Conventional software management practices are sound in theory, but practice is still tied to
archaic (outdated) technology and techniques.
Conventional software economics provides a benchmark of performance for
conventional software management principles.
The best thing about software is its flexibility: It can be programmed to do almost anything.
The worst thing about software is also its flexibility: The "almost anything"
characteristic has made it difficult to plan, monitors, and control software development.
Three important analyses of the state of the software engineering industry are
1. Software development is still highly unpredictable. Only about 10% of
software projects are delivered successfully within initial budget and schedule
estimates.
2. Management discipline is more of a discriminator in success or failure than are
technology advances.
3. The level of software scrap and rework is indicative of an immature process.
All three analyses reached the same general conclusion: The success rate for software
projects is very low. The three analyses provide a good introduction to the magnitude
of the software problem and the current norms for conventional software management
performance.
THE WATERFALL MODEL
Most software engineering texts present the waterfall model as the source of the
"conventional" software process.
IN THEORY
It provides an insightful and concise summary of conventional
software management Three main primary points are
1. There are two essential steps common to the development of computer programs:
analysis and
coding.
Waterfall Model part 1: The two basic steps to building a program.
2. In order to manage and control all of the intellectual freedom associated with
software development, one must introduce several other "overhead" steps,
including system requirements definition, software requirements definition,
program design, and testing. These steps supplement the analysis and coding
steps. Below Figure illustrates the resulting project profile and the basic steps in
developing a large-scale program.
Coding
Analysis Analysis and coding both involve creative work that
directly contributes to the usefulness of the end
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all model is ri
T
esting
Operation
3. The basic framework described in the waterfsky and invites failure. The testing phasethat
occurs at the end of the development cycle is the first event for which timing, storage, input/output
transfers, etc., are experienced as distinguished from analyzed. The resulting design changes are
likely to be so disruptive that the software requirements upon which the design is based are likely
violated. Either the requirements must be modified or a substantial design change is warranted.
Five necessary improvements for waterfall model are:-
1. Program design comes first. Insert a preliminary program design phase
between the software requirements generation phase and the analysis phase. By
this technique, the program designer assures that the software will not fail
because of storage, timing, and data flux (continuous change). As analysis
proceeds in the succeeding phase, the program designer must impose on the
analyst the storage, timing, and operational constraints in such a way that he
senses the consequences. If the total resources to be applied are insufficient or if
the embryonic(in an early stage of development) operational design is wrong, it
will be recognized at this early stage and the iteration with requirements and
preliminary design can be redone before final design, coding, and test
commences. How is this program design procedure implemented?
The following steps are required:
Begin the design process with program designers, not analysts or programmers.
Design, define, and allocate the data processing modes even at the risk of
being wrong. Allocate processing functions, design the database, allocate
execution time, define interfaces and processing modes with the operating
system, describe input and output processing, and define preliminary
operating procedures.
Write an overview document that is understandable, informative, and current
so that every worker on the project can gain an elemental understanding of
the system.
2. Document the design. The amount of documentation required on most software
programs is quite a lot, certainly much more than most programmers, analysts, or
program designers are willing to do if left to their own devices. Why do we need so
Requirement
Analysis
Coding
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much documentation? (1) Each designer must communicate with interfacing designers,
managers, and possibly customers. (2) During early phases, the documentation is the
design. (3) The real monetary value of documentation is to support later modifications by
a separate test team, a separate maintenance team, and operations personnel who are not
software literate.
3. Do it twice. If a computer program is being developed for the first time, arrange
matters so that the version finally delivered to the customer for operational
deployment is actually the second version insofar as critical design/operations are
concerned. Note that this is simply the entire process done in miniature, to a time scale
that is relatively small with respect to the overall effort. In the first version, the team
must have a special broad competence where they can quickly sense trouble spots in
the design, model them, model alternatives, forget the straightforward aspects of the
design that aren't worth studying at this early point, and, finally, arrive at an error-free
program.
4. Plan, control, and monitor testing. Without question, the biggest user of project
resources-manpower, computer time, and/or management judgment-is the test phase.
This is the phase of greatest risk in terms of cost and schedule. It occurs at the latest
point in the schedule, when backup alternatives are least available, if at all. The
previous three recommendations were all aimed at uncovering and solving problems
before entering the test phase. However, even after doing these things, there is still a
test phase and there are still important things to be done, including: (1) employ a team
of test specialists who were not responsible for the
original design; (2) employ visual inspections to spot the obvious errors like dropped
minus signs, missing factors of two, jumps to wrong addresses (do not use the computer to
detect this kind of thing, it is too expensive); (3) test every logic path; (4) employ the final
checkout on the target computer.
5. Involve the customer. It is important to involve the customer in a formal way so that
he has committed himself at earlier points before final delivery. There are three points
following requirements definition where the insight, judgment, and commitment of the
customer can bolster the development effort. These include a "preliminary software
review" following the preliminary program design step, a sequence of "critical software
design reviews" during program design, and a "final software acceptance review".
IN PRACTICE
Some software projects still practice the conventional software management approach.
It is useful to summarize the characteristics of the conventional process as it has
typically been applied, which is not necessarily as it was intended. Projects destined for
trouble frequently exhibit the following symptoms:
 Protracted integration and late design breakage.
 Late risk resolution.
 Requirements-driven functional decomposition.
 Adversarial (conflict or opposition) stakeholder relationships.
 Focus on documents and review meetings.
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Protracted Integration and Late Design Breakage
For a typical development project that used a waterfall model management process, Figure
1-2 illustrates development progress versus time. Progress is defined as percent coded, that
is, demonstrable in its target form.
The following sequence was common:
 Early success via paper designs and thorough (often too thorough) briefings.
 Commitment to code late in the life cycle.
 Integration nightmares (unpleasant experience) due to unforeseen
implementation issues and interface ambiguities.
 Heavy budget and schedule pressure to get the system working.
 Late shoe-homing of no optimal fixes, with no time for redesign.
 A very fragile, unmentionable product delivered late.
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In the conventional model, the entire system was designed on paper, then implemented all at once, then
integrated. Table 1-1 provides a typical profile of cost expenditures across the spectrum of software
activities.
Late risk resolution A serious issue associated with the waterfall lifecycle was the lack of early risk
resolution. Figure 1.3 illustrates a typical risk profile for conventional waterfall model projects. It includes
four distinct periods of risk exposure, where risk is defined as the probability of missing a cost, schedule,
feature, or quality goal. Early in the life cycle, as the requirements were being specified, the actual risk
exposure was highly unpredictable.
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Requirements-Driven Functional Decomposition: This approach depends on specifying requirements
completely and unambiguously before other development activities begin. It naively treats all
requirements as equally important, and depends on those requirements remaining constant over the software
development life cycle. These conditions rarely occur in the real world. Specification of requirements is a
difficult and important part of the software development process.
Another property of the conventional approach is that the requirements were typically specified in a
functional manner. Built into the classic waterfall process was the fundamental assumption that the software
itself was decomposed into functions; requirements were then allocated to the resulting components. This
decomposition was often very different from a decomposition based on object-oriented design and the use of
existing components. Figure 1-4 illustrates the result of requirements-driven approaches: a software
structure that is organized around the requirements specification structure.
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Adversarial Stakeholder Relationships:
The conventional process tended to result in adversarial stakeholder relationships, in large part because of
the difficulties of requirements specification and the exchange of information solely through paper
documents that captured engineering information in ad hoc formats.
The following sequence of events was typical for most contractual software efforts:
1. The contractor prepared a draft contract-deliverable document that captured an intermediate
artifact and delivered it to the customer for approval.
2. The customer was expected to provide comments (typically within 15 to 30 days).
3. The contractor incorporated these comments and submitted (typically within 15 to 30 days) a final
version for approval.
This one-shot review process encouraged high levels of sensitivity on the part of customers and contractors.
Focus on Documents and Review Meetings:
The conventional process focused on producing various documents that attempted to describe the software
product, with insufficient focus on producing tangible increments of the products themselves. Contractors
were driven to produce literally tons of paper to meet milestones and demonstrate progress to stakeholders,
rather than spend their energy on tasks that would reduce risk and produce quality software. Typically,
presenters and the audience reviewed the simple things that they understood rather than the complex and
important issues. Most design reviews therefore resulted in low engineering value and high cost in terms of
the effort and schedule involved in their preparation and conduct. They presented merely a facade of
progress.
Table 1-2 summarizes the results of a typical design review.
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CONVENTIONAL SOFTWARE MANAGEMENT PERFORMANCE
Barry Boehm's "Industrial Software Metrics Top 10 List= is a good, objective characterization of the state of
software development.
1. Finding and fixing a software problem after delivery costs 100 times more than finding and fixing the
problem in early design phases.
2. You can compress software development schedules 25% of nominal, but no more.
3. For every $1 you spend on development, you will spend $2 on maintenance.
4. Software development and maintenance costs are primarily a function of the number of source
lines of code.
5. Variations among people account for the biggest differences in software productivity.
6. The overall ratio of software to hardware costs is still growing. In 1955 it was 15:85; in 1985, 85:15.
7. Only about 15% of software development effort is devoted to programming.
8. Software systems and products typically cost 3 times as much per SLOC as individual software
programs. Software-system products (i.e., system of systems) cost 9 times as much.
9. Walkthroughs catch 60% of the errors
10. 80% of the contribution comes from 20% of the contributors.
2.Evolution of SoftwareEconomics
SOFTWARE ECONOMICS
Most software cost models can be abstracted into a function of five basic parameters: size, process,
personnel, environment, and required quality.
1. The size of the end product (in human-generated components), which is typically quantified in
terms of the number of source instructions or the number of function points required to develop
the required functionality
2. The process used to produce the end product, in particular the ability of the process to avoid non-
value-adding activities (rework, bureaucratic delays, communications overhead)
3. The capabilities of software engineering personnel, and particularly their experience with the
computer science issues and the applications domain issues of the project
4. The environment, which is made up of the tools and techniques available to support efficient
software development and to automate the process
5. The required quality of the product, including its features, performance, reliability, and
adaptability The relationships among these parameters and the estimated cost can be written as
follows:
Effort = (Personnel) (Environment) (Quality) ( Sizeprocess
)
One important aspect of software economics (as represented within today's software cost models) is
that the relationship between effort and size exhibits a diseconomy of scale. The diseconomy of scale of
software development is a result of the process exponent being greater than 1.0. Contrary to most
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manufacturing processes, the more software you build, the more expensive it is per unit item.
Figure 2-1 shows three generations of basic technology advancement in tools, components, and
processes. The required levels of quality and personnel are assumed to be constant. The ordinate of the
graph refers to software unit costs (pick your favorite: per SLOC, per function point, per component)
realized by an organization.
The three generations of software development are defined as follows:
1) Conventional: 1960s and 1970s, craftsmanship. Organizations used custom tools, custom
processes, and virtually all custom components built in primitive languages. Project performance
was highly predictable in that cost, schedule, and quality objectives were almost always
underachieved.
2) Transition: 1980s and 1990s, software engineering. Organiz:1tions used more-repeatable processes and
off- the-shelf tools, and mostly (>70%) custom components built in higher level languages. Some of
the
components (<30%) were available as commercial products, including the operating system, database
management system, networking, and graphical user interface.
3) Modern practices: 2000 and later, software production. This book's philosophy is rooted in
the use of managed and measured processes, integrated automation environments, and
mostly (70%) off-the-shelf components. Perhaps as few as 30% of the components need to
be custom built
Technologies for environment automation, size reduction, and process improvement are not
independent of one another. In each new era, the key is complementary growth in all technologies. For
example, the process advances could not be used successfully without new component technologies and
increased tool automation.
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Organizations are achieving better economies of scale in successive technology eras-with very large projects
(systems of systems), long-lived products, and lines of business comprising multiple similar projects. Figure
2-2 provides an overview of how a return on investment (ROI) profile can be achieved in subsequent efforts
across life cycles of various domains.
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PRAGMATIC SOFTWARE COST ESTIMATION
One critical problem in software cost estimation is a lack of well-documented case studies of projects that
used an iterative development approach. Software industry has inconsistently defined metrics or atomic
units of measure, the data from actual projects are highly suspect in terms of consistency and comparability.
It is hard enough to collect a homogeneous set of project data within one organization; it is extremely
difficult to homog- enize data across different organizations with different processes, languages, domains,
and so on.
There have been many debates among developers and vendors of software cost estimation models and tools.
Three topics of these debates are of particular interest here:
1. Which cost estimation model to use?
2. Whether to measure software size in source lines of code or function points.
3. What constitutes a good estimate?
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There are several popular cost estimation models (such as COCOMO, CHECKPOINT, ESTIMACS,
KnowledgePlan, Price-S, ProQMS, SEER, SLIM, SOFTCOST, and SPQR/20), CO COMO is also one of
the most open and well-documented cost estimation models. The general accuracy of conventional cost
models
(such as COCOMO) has been described as "within 20% of actuals, 70% of the time."
Most real-world use of cost models is bottom-up (substantiating a target cost) rather than top-down
(estimating the "should" cost). Figure 2-3 illustrates the predominant practice: The software project manager
defines the target cost of the software, and then manipulates the parameters and sizing until the target cost
can be justified. The rationale for the target cost maybe to win a proposal, to solicit customer funding, to
attain internal corporate funding, or to achieve some other goal.
The process described in Figure 2-3 is not all bad. In fact, it is absolutely necessary to analyze the cost risks
and understand the sensitivities and trade-offs objectively. It forces the software project manager to
examine the risks associated with achieving the target costs and to discuss this information with other
stakeholders.
A good software cost estimate has the following attributes:
 It is conceived and supported by the project manager, architecture team, development team, and
test team accountable for performing the work.
 It is accepted by all stakeholders as ambitious but realizable.
 It is based on a well-defined software cost model with a credible basis.
 It is based on a database of relevant project experience that includes similar processes, similar
technologies, similar environments, similar quality requirements, and similar people.
 It is defined in enough detail so that its key risk areas are understood and the probability of success
is objectively assessed.
Extrapolating from a good estimate, an ideal estimate would be derived from a mature cost model with an
experience base that reflects multiple similar projects done by the same team with the same mature
processes and tools.
3. Improving Software Economics
Five basic parameters of the software cost model are
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1.Reducing the size or complexity of what needs to be developed.
2. Improving the development process.
3. Using more-skilled personnel and better teams (not necessarily the same thing).
4. Using better environments (tools to automate the process).
5. Trading off or backing off on quality thresholds.
These parameters are given in priority order for most software domains. Table 3-1 lists some of the
technology developments, process improvement efforts, and management approaches targeted at
improving the economics of software development and integration.
REDUCING SOFTWARE PRODUCT SIZE
The most significant way to improve affordability and return on investment (ROI) is usually to produce a
product that achieves the design goals with the minimum amount of human-generated source material.
Component-based development is introduced as the general term for reducing the "source" language size
to achieve a software solution.
Reuse, object-oriented technology, automatic code production, and higher order programming languages
are all focused on achieving a given system with fewer lines of human-specified source directives
(statements).
size reduction is the primary motivation behind improvements in higher order languages (such as C++, Ada
95, Java, Visual Basic), automatic code generators (CASE tools, visual modeling tools, GUI builders), reuse
of commercial components (operating systems, windowing environments, database management systems,
middleware, networks), and object-oriented technologies (Unified Modeling Language, visual modeling
tools, architecture frameworks).
The reduction is defined in terms of human-generated source material. In general, when size-reducing
technologies are used, they reduce the number of human-generated source lines.
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LANGUAGES
Universal function points (UFPs1
) are useful estimators for language-independent, early life-cycle
estimates. The basic units of function points are external user inputs, external outputs, internal logical data
groups, external data interfaces, and external inquiries. SLOC metrics are useful estimators for software
after a candidate solution is formulated and an implementation language is known. Substantial data have
been documented relating SLOC to function points. Some of these results are shown in Table 3-2.
Languages expressiveness of some of today9s popular languages
1 Function point metrics provide a standardized method for measuring the various functions of a software
application.
The basic units of function points are external user inputs, external outputs, internal logical data groups,
external data interfaces, and external inquiries.
Assembly 320
C 128
FORTAN77 105
COBOL85 91
Ada83 71
C++ 56
Ada95 55
Java 55
Visual Basic 35
Table 3-2
OBJECT-ORIENTED METHODS AND VISUAL MODELING
Object-oriented technology is not germane to most of the software management topics discussed here, and
books on object-oriented technology abound. Object-oriented programming languages appear to benefit
both software productivity and software quality. The fundamental impact of object-oriented technology is
in reducing the overall size of what needs to be developed.
People like drawing pictures to explain something to others or to themselves. When they do it for
software system design, they call these pictures diagrams or diagrammatic models and the very
notation for them a modeling language.
These are interesting examples of the interrelationships among the dimensions of improving software eco-
nomics.
1. An object-oriented model of the problem and its solution encourages a common vocabulary
between the end users of a system and its developers, thus creating a shared understanding of the
problem being solved.
2. The use of continuous integration creates opportunities to recognize risk early and make incremental
LANGUAGES SLOC per UFP
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corrections without destabilizing the entire development effort.
3. An object-oriented architecture provides a clear separation of concerns among disparate elements
of a system, creating firewalls that prevent a change in one part of the system from rending the
fabric of the entire architecture.
Booch also summarized five characteristics of a successful object-oriented project.
1. A ruthless focus on the development of a system that provides a well understood collection of essential
minimal characteristics.
2. The existence of a culture that is centered on results, encourages communication, and yet is not
afraid to fail.
3. The effective use of object-oriented modeling.
4. The existence of a strong architectural vision.
5. The application of a well-managed iterative and incremental development life cycle.
REUSE
Reusing existing components and building reusable components have been natural software engineering
activities since the earliest improvements in programming languages. With reuse in order to minimize
development costs while achieving all the other required attributes of performance, feature set, and quality.
Try to treat reuse as a mundane part of achieving a return on investment.
Most truly reusable components of value are transitioned to commercial products supported by
organizations with the following characteristics:
 They have an economic motivation for continued support.
 They take ownership of improving product quality, adding new features, and transitioning to new
technologies.
 They have a sufficiently broad customer base to be profitable.
The cost of developing a reusable component is not trivial. Figure 3-1 examines the economic trade-offs.
The steep initial curve illustrates the economic obstacle to developing reusable components.
Reuse is an important discipline that has an impact on the efficiency of all workflows and the quality of most
artifacts.
COMMERCIAL COMPONENTS
A common approach being pursued today in many domains is to maximize integration of commercial
components and off-the-shelf products. While the use of commercial components is certainly desirable as a
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means of reducing custom development, it has not proven to be straightforward in practice. Table 3-3
identifies some of the advantages and disadvantages of using commercial components.
IMPROVING SOFTWARE PROCESSES
Process is an overloaded term. Three distinct process perspectives are.
 Metaprocess: an organization's policies, procedures, and practices for pursuing a software-
intensive line of business. The focus of this process is on organizational economics, long-term
strategies, and software ROI.
 Macroprocess: a project's policies, procedures, and practices for producing a complete software
product within certain cost, schedule, and quality constraints. The focus of the macro process is on
creating an adequate instance of the Meta process for a specific set of constraints.
 Microprocess: a project team's policies, procedures, and practices for achieving an artifact of the
software process. The focus of the micro process is on achieving an intermediate product baseline
with adequate quality and adequate functionality as economically and rapidly as practical.
Although these three levels of process overlap somewhat, they have different objectives, audiences,
metrics, concerns, and time scales as shown in Table 3-4
In a perfect software engineering world with an immaculate problem description, an obvious solution
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space, a development team of experienced geniuses, adequate resources, and stakeholders with common
goals, we could execute a software development process in one iteration with almost no scrap and rework.
Because we work in an imperfect world, however, we need to manage engineering activities so that scrap
and rework profiles do not have an impact on the win conditions of any stakeholder. This should be the
underlying premise for most process improvements.
IMPROVING TEAM EFFECTIVENESS
Teamwork is much more important than the sum of the individuals. With software teams, a project manager
needs to configure a balance of solid talent with highly skilled people in the leverage positions. Some
maxims of team management include the following:
 A well-managed project can succeed with a nominal engineering team.
 A mismanaged project will almost never succeed, even with an expert team of engineers.
 A well-architected system can be built by a nominal team of software builders.
 A poorly architected system will flounder even with an expert team of builders.
Boehm five staffing principles are
1. The principle of top talent: Use better and fewer people
2. The principle of job matching: Fit the tasks to the skills and motivation of the people available.
3. The principle of career progression: An organization does best in the long run by helping its
people to self-actualize.
4. The principle of team balance: Select people who will complement and harmonize with one another
5. The principle of phase-out: Keeping a misfit on the team doesn't benefit anyone
Software project managers need many leadership qualities in order to enhance team effectiveness. The
following are some crucial attributes of successful software project managers that deserve much more
attention:
1. Hiring skills. Few decisions are as important as hiring decisions. Placing the right person in the
right job seems obvious but is surprisingly hard to achieve.
2. Customer-interface skill. Avoiding adversarial relationships among stakeholders is a prerequisite
for success.
Decision-making skill. The jillion books written about management have failed to provide a clear
definition of this attribute. We all know a good leader when we run into one, and decision-making
skill seems obvious despite its intangible definition.
Team-building skill. Teamwork requires that a manager establish trust, motivate progress, exploit
eccentric prima donnas, transition average people into top performers, eliminate misfits, and
consolidate diverse opinions into a team direction.
Selling skill. Successful project managers must sell all stakeholders (including themselves) on
decisions and priorities, sell candidates on job positions, sell changes to the status quo in the face of
resistance, and sell achievements against objectives. In practice, selling requires continuous
negotiation, compromise, and empathy
IMPROVING AUTOMATION THROUGH SOFTWARE ENVIRONMENTS
The tools and environment used in the software process generally have a linear effect on the
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productivity of the process. Planning tools, requirements management tools, visual modeling tools,
compilers, editors, debuggers, quality assurance analysis tools, test tools, and user interfaces provide crucial
automation support for evolving the software engineering artifacts. Above all, configuration management
environments provide the foundation for executing and instrument the process. At first order, the isolated
impact of tools and automation generally allows improvements of 20% to 40% in effort. However, tools and
environments must be viewed as the primary delivery vehicle for process automation and improvement, so
their impact can be much higher.
Automation of the design process provides payback in quality, the ability to estimate costs and
schedules, and overall productivity using a smaller team.
Round-trip engineering describe the key capability of environments that support iterative development. As
we have moved into maintaining different information repositories for the engineering artifacts, we need
automation support to ensure efficient and error-free transition of data from one artifact to another. Forward
engineering is the automation of one engineering artifact from another, more abstract representation. For
example, compilers and linkers have provided automated transition of source code into executable code.
Reverse engineering is the generation or modification of a more abstract representation from an existing
artifact (for example, creating a .visual design model from a source code representation).
Economic improvements associated with tools and environments. It is common for tool vendors to make
relatively accurate individual assessments of life-cycle activities to support claims about the potential
economic impact of their tools. For example, it is easy to find statements such as the following from
companies in a particular tool.
 Requirements analysis and evolution activities consume 40% of life-cycle costs.
 Software design activities have an impact on more than 50% of the resources.
 Coding and unit testing activities consume about 50% of software development effort and schedule.
 Test activities can consume as much as 50% of a project's resources.
 Configuration control and change management are critical activities that can consume as much as
25% of resources on a large-scale project.
 Documentation activities can consume more than 30% of project engineering resources.
 Project management, business administration, and progress assessment can consume as much as
30% of project budgets.
ACHIEVING REQUIRED QUALITY
Software best practices are derived from the development process and technologies. Table 3-5 summarizes
some dimensions of qualityimprovement.
Key practices that improve overall software quality include the following:
Focusing on driving requirements and critical use cases early in the life cycle, focusing on
requirements completeness and traceability late in the life cycle, and focusing throughout the life
cycle on a balance between requirements evolution, design evolution, and plan evolution
Using metrics and indicators to measure the progress and quality of an architecture as it evolves
from a high-level prototype into a fully compliant product
Providing integrated life-cycle environments that support early and continuous configuration
control, change management, rigorous design methods, document automation, and regression test
automation
Using visual modeling and higher level languages that support architectural control, abstraction,
reliable programming, reuse, and self-documentation
Early and continuous insight into performance issues through demonstration-based evaluations
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Conventional development processes stressed early sizing and timing estimates of computer program
resource utilization. However, the typical chronology of events in performance assessment was as
follows
Project inception. The proposed design was asserted to be low risk with adequate performance
margin.
Initial design review. Optimistic assessments of adequate design margin were based mostly on
paper analysis or rough simulation of the critical threads. In most cases, the actual application
algorithms and database sizes were fairly well understood.
Mid-life-cycle design review. The assessments started whittling away at the margin, as early
benchmarks and initial tests began exposing the optimism inherent in earlier estimates.
Integration and test. Serious performance problems were uncovered, necessitating fundamental
changes in the architecture. The underlying infrastructure was usually the scapegoat, but the real
culprit was immature use of the infrastructure, immature architectural solutions, or poorly
understood early design trade-offs.
PEER INSPECTIONS: A PRAGMATICVIEW
Peer inspections are frequently over hyped as the key aspect of a quality system. In my experience, peer
reviews are valuable as secondary mechanisms, but they are rarely significant contributors to quality
compared with the following primary quality mechanisms and indicators, which should be emphasized in
the management process:
 Transitioning engineering information from one artifact set to another, thereby assessing the
consistency, feasibility, understandability, and technology constraints inherent in the engineering
artifacts
 Major milestone demonstrations that force the artifacts to be assessed against tangible criteria in
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the context of relevant use cases
 Environment tools (compilers, debuggers, analyzers, automated test suites) that ensure
representation rigor, consistency, completeness, and change control
 Life-cycle testing for detailed insight into critical trade-offs, acceptance criteria, and requirements
compliance
 Change management metrics for objective insight into multiple-perspective change trends and
convergence or divergence from quality and progress goals
Inspections are also a good vehicle for holding authors accountable for quality products. All authors of
software and documentation should have their products scrutinized as a natural by-product of the
process. Therefore, the coverage of inspections should be across all authors rather than across all
components.
THE OLD WAY AND THE NEW
THE PRINCIPLES OF CONVENTIONAL SOFTWARE ENGINEERING
1.Make quality #1. Quality must be quantified and mechanisms put into place to motivate its achievement
2.High-quality software is possible. Techniques that have been demonstrated to increase quality include
involving the customer, prototyping, simplifying design, conducting inspections, and hiring the best people
3.Give products to customers early. No matter how hard you try to learn users' needs during the
requirements phase, the most effective way to determine real needs is to give users a product and let them
play with it 4.Determine the problem before writing the requirements. When faced with what they
believe is a problem, most engineers rush to offer a solution. Before you try to solve a problem, be sure to
explore all the alternatives and don't be blinded by the obvious solution
5.Evaluate design alternatives. After the requirements are agreed upon, you must examine a variety of
architectures and algorithms. You certainly do not want to use= architecture" simply because it was used in
the requirements specification.
6.Use an appropriate process model. Each project must select a process that makes ·the most sense for that
project on the basis of corporate culture, willingness to take risks, application area, volatility of
requirements, and the extent to which requirements are well understood.
7.Use different languages for different phases. Our industry's eternal thirst for simple solutions to
complex problems has driven many to declare that the best development method is one that uses the same
notation throughout the life cycle.
8.Minimize intellectual distance. To minimize intellectual distance, the software's structure should be as
close as possible to the real-world structure
9.Put techniques before tools. An undisciplined software engineer with a tool becomes a dangerous,
undisciplined software engineer
10. Get it right before you make it faster. It is far easier to make a working program run faster than it is to
make a fast program work. Don't worry about optimization during initial coding
11. Inspect code. Inspecting the detailed design and code is a much better way to find errors than testing
12.Good management is more important than good technology. Good management motivates people to
do their best, but there are no universal "right" styles of management.
13.People are the key to success. Highly skilled people with appropriate experience, talent, and training are
key.
14.Follow with care. Just because everybody is doing something does not make it right for you. It may be
right, but you must carefully assess its applicability to your environment.
15.Take responsibility. When a bridge collapses we ask, "What did the engineers do wrong?" Even when
software fails, we rarely ask this. The fact is that in any engineering discipline, the best methods can be used
to produce awful designs, and the most antiquated methods to produce elegant designs.
16.Understand the customer's priorities. It is possible the customer would tolerate 90% of the
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functionality delivered late if they could have 10% of it on time.
17.The more they see, the more they need. The more functionality (or performance) you provide a user,
the more functionality (or performance) the user wants.
18. Plan to throw one away. One of the most important critical success factors is whether or not a product is
entirely new. Such brand-new applications, architectures, interfaces, or algorithms rarely work the first
time.
19. Design for change. The architectures, components, and specification techniques you use must
accommodate change.
20. Design without documentation is not design. I have often heard software engineers say, "I have
finished the design. All that is left is the documentation. "
21. Use tools, but be realistic. Software tools make their users more efficient.
22. Avoid tricks. Many programmers love to create programs with tricks constructs that perform a function
correctly, but in an obscure way. Show the world how smart you are by avoiding tricky code
23. Encapsulate. Information-hiding is a simple, proven concept that results in software that is easier
to test and much easier to maintain.
24. Use coupling and cohesion. Coupling and cohesion are the best ways to measure software's inherent
maintainability and adaptability
25. Use the McCabe complexity measure. Although there are many metrics available to report the inherent
complexity of software, none is as intuitive and easy to use as Tom McCabe's
26. Don't test your own software. Software developers should never be the primary testers of their
own software.
27.Analyze causes for errors. It is far more cost-effective to reduce the effect of an error by preventing it
than it is to find and fix it. One way to do this is to analyze the causes of errors as they are detected
28.Realize that software's entropy increases. Any software system that undergoes continuous change will
grow in complexity and will become more and more disorganized
29.People and time are not interchangeable. Measuring a project solely by person-months makes little
sense 30.Expect excellence. Your employees will do much better if you have high expectations for them.
THE PRINCIPLES OF MODERN SOFTWARE MANAGEMENT
Top 10 principles of modern software management are. (The first five, which are the main themes of
my definition of an iterative process, are summarized in Figure 4-1.)
Base the process on an architecture-first approach. This requires that a demonstrable balance be
achieved among the driving requirements, the architecturally significant design decisions, and the
life- cycle plans before the resources are committed for full-scale development.
Establish an iterative life-cycle process that confronts risk early. With today's sophisticated
software systems, it is not possible to define the entire problem, design the entire solution, build the
software, and then test the end product in sequence. Instead, an iterative process that refines the
problem understanding, an effective solution, and an effective plan over several iterations encourages
a balanced treatment of all stakeholder objectives. Major risks must be addressed early to increase
predictability and avoid expensive downstream scrap and rework.
Transition design methods to emphasize component-based development. Moving from a line-of-
code mentality to a component-based mentality is necessary to reduce the amount of human-
generated source code and custom development.
4. Establish a change management environment. The dynamics of iterativedevelopment,
including concurrent workflows by different teams working on shared artifacts, necessitates
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objectively controlled baselines.
5. Enhance change freedom through tools that support round-trip engineering. Round-
trip engineering is the environment support necessary to automate and synchronize
engineering information in different formats(such as requirements specifications, design
models, source code, executable code, test cases).
6. Capture design artifacts in rigorous, model-based notation. A model based approach (such as
UML) supports the evolution of semantically rich graphical and textual design notations.
7. Instrument the process for objective quality control and progress assessment. Life-cycle
assessment of the progress and the quality of all intermediate products must be integrated into the process.
8. Use a demonstration-based approach to assess intermediate artifacts.
9. Plan intermediate releases in groups of usage scenarios with evolving levels of detail. It is
essential that the software management process drive toward early and continuous
demonstrations within the operational context of the system, namely its use cases.
10. Establish a configurable process that is economically scalable. No single process is
suitable for all software developments.
Table 4-1 maps top 10 risks of the conventional process to the key attributes and principles of a modern
process
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TRANSITIONING TO AN ITERATIVE PROCESS
Modern software development processes have moved away from the conventional waterfall model, in
which each stage of the development process is dependent on completion of the previous stage.
The economic benefits inherent in transitioning from the conventional waterfall model to an iterative
development process are significant but difficult to quantify. As one benchmark of the expected economic
impact of process improvement, consider the process exponent parameters of the COCOMO II model.
(Appendix B provides more detail on the COCOMO model) This exponent can range from 1.01 (virtually
no diseconomy of scale) to 1.26 (significant diseconomy of scale). The parameters that govern the value
of the process exponent are application precedentedness, process flexibility, architecture risk resolution,
team cohesion, and software process maturity.
The following paragraphs map the process exponent parameters of CO COMO II to my top 10
principles of a modern process.
 Application precedentedness. Domain experience is a critical factor in understanding how to plan
and execute a software development project. For unprecedented systems, one of the key goals is to
confront risks and establish early precedents, even if they are incomplete or experimental. This is one
of the primary reasons that the software industry has moved to an iterative life-cycle process. Early
iterations in the life cycle establish precedents from which the product, the process, and the plans can
be elaborated in evolving levels of detail.
 Process flexibility. Development of modern software is characterized by such a broad solution
space and so many interrelated concerns that there is a paramount need for continuous incorporation
of changes. These changes may be inherent in the problem understanding, the solution space, or the
plans. Project artifacts must be supported by efficient change management commensurate with
project needs. A configurable process that allows a common framework to be adapted across a
range of projects is necessary to achieve a software return on investment.
 Architecture risk resolution. Architecture-first development is a crucial theme underlying a
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successful iterative development process. A project team develops and stabilizes architecture before
developing all the components that make up the entire suite of applications components. An
architecture-first and component-based development approach forces the infrastructure, common
mechanisms, and control mechanisms to be elaborated early in the life cycle and drives all component
make/buy decisions into the architecture process.
 Team cohesion. Successful teams are cohesive, and cohesive teams are successful. Successful teams
and cohesive teams share common objectives and priorities. Advances in technology (such as
programming languages, UML, and visual modeling) have enabled more rigorous and
understandable notations for communicating software engineering information, particularly in the
requirements and design artifacts that previously were ad hoc and based completely on paper
exchange. These model- based formats have also enabled the round-trip engineering support
needed to establish change freedom sufficient for evolving design representations.
 Software process maturity. The Software Engineering Institute's Capability Maturity Model
(CMM) is a well-accepted benchmark for software process assessment. One of key themes is that
truly mature processes are enabled through an integrated environment that provides the appropriate
level of automation to instrument the process for objective quality control.
Life-Cycle Phases and Process artifacts
Life cycle phases
Characteristic of a successful software development process is the well-defined separation between
"research and development" activities and "production" activities. Most unsuccessful projects exhibit one
of the following characteristics:
 An overemphasis on research and development
 An overemphasis on production.
Successful modern projects-and even successful projects developed under the conventional process-tend
to have a very well-defined project milestone when there is a noticeable transition from a research attitude
to a production attitude. Earlier phases focus on achieving functionality. Later phases revolve around
achieving a product that can be shipped to a customer, with explicit attention to robustness, performance,
and finish.
A modern software development process must be defined to support the following:
 Evolution of the plans, requirements, and architecture, together with well defined
synchronization points
 Risk management and objective measures of progress and quality
 Evolution of system capabilities through demonstrations of increasing functionality
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ENGINEERING AND PRODUCTION STAGES
To achieve economies of scale and higher returns on investment, we must move toward a software
manufacturing process driven by technological improvements in process automation and component-
based development. Two stages of the life cycle are:
1. The engineering stage, driven by less predictable but smaller teams doing design and
synthesis activities
2. The production stage, driven by more predictable but larger teams doing construction, test,
and deployment activities
The transition between engineering and production is a crucial event for the various stakeholders.
The production plan has been agreed upon, and there is a good enough understanding of the problem and
the solution that all stakeholders can make a firm commitment to go ahead with production.
Engineering stage is decomposed into two distinct phases, inception and elaboration, and the production
stage into construction and transition. These four phases of the life-cycle process are loosely mapped to
the conceptual framework of the spiral model as shown in Figure 5-1
INCEPTION PHASE
The overriding goal of the inception phase is to achieve concurrence among stakeholders on the life-
cycle objectives for the project.
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PRIMARY OBJECTIVES
 Establishing the project's software scope and boundary conditions, including an operational
concept, acceptance criteria, and a clear understanding of what is and is not intended to be in the
product
 Discriminating the critical use cases of the system and the primary scenarios of operation that
will drive the major design trade-offs
 Demonstrating at least one candidate architecture against some of the primary scenanos
 Estimating the cost and schedule for the entire project (including detailed estimates for
the elaboration phase)
 Estimating potential risks (sources of unpredictability)
ESSENTIAL ACTMTIES
 Formulating the scope of the project. The information repository should be sufficient to define
the problem space and derive the acceptance criteria for the end product.
 Synthesizing the architecture. An information repository is created that is sufficient to
demonstrate the feasibility of at least one candidate architecture and an, initial baseline of
make/buy decisions so that the cost, schedule, and resource estimates can be derived.
 Planning and preparing a business case. Alternatives for risk management, staffing, iteration
plans, and cost/schedule/profitability trade-offs are evaluated.
PRIMARY EVALUATION CRITERIA
 Do all stakeholders concur on the scope definition and cost and schedule estimates?
 Are requirements understood, as evidenced by the fidelity of the critical use cases?
 Are the cost and schedule estimates, priorities, risks, and development processes credible?
 Do the depth and breadth of an architecture prototype demonstrate the preceding criteria? (The
primary value of prototyping candidate architecture is to provide a vehicle for understanding the
scope and assessing the credibility of the development group in solving the particular technical
problem.)
 Are actual resource expenditures versus planned expenditures acceptable
ELABORATION PHASE
At the end of this phase, the "engineering" is considered complete. The elaboration phase activities must
ensure that the architecture, requirements, and plans are stable enough, and the risks sufficiently
mitigated, that the cost and schedule for the completion of the development can be predicted within an
acceptable range. During the elaboration phase, an executable architecture prototype is built in one or
more iterations, depending on the scope, size, & risk.
PRIMARY OBJECTIVES
 Baselining the architecture as rapidly as practical (establishing a configuration-managed snapshot in
which all changes are rationalized, tracked, and maintained)
 Baselining the vision
 Baselining a high-fidelity plan for the construction phase
 Demonstrating that the baseline architecture will support the vision at a reasonable cost in a
reasonable time
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ESSENTIAL ACTIVITIES
 Elaborating the vision.
 Elaborating the process and infrastructure.
 Elaborating the architecture and selecting components.
 Is the vision stable?
 Is the architecture stable?
 Does the executable demonstration show that the major risk elements have been addressed and
credibly resolved?
 Is the construction phase plan of sufficient fidelity, and is it backed up with a credible basis of
estimate?
 Do all stakeholders agree that the current vision can be met if the current plan is executed to develop
the complete system in the context of the current architecture?
 Are actual resource expenditures versus planned expenditures acceptable?
CONSTRUCTION PHASE
During the construction phase, all remaining components and application features are integrated
into the application, and all features are thoroughly tested. Newly developed software is integrated
where required. The construction phase represents a production process, in which emphasis is placed
on managing resources and controlling operations to optimize costs, schedules, and quality.
PRIMARY OBJECTIVES
Minimizing development costs by optimizing resources and avoiding unnecessary scrap and
rework
Achieving adequate quality as rapidly as practical
Achieving useful versions (alpha, beta, and other test releases) as rapidly as practical
Resource management, control, and process optimization
Complete component development and testing against evaluation criteria
Assessment of product releases against acceptance criteria of the vision
Is this product baseline mature enough to be deployed in the user community? (Existing defects
are not obstacles to achieving the purpose of the next release.)
Is this product baseline stable enough to be deployed in the user community? (Pending changes
are not obstacles to achieving the purpose of the next release.)
Are the stakeholders ready for transition to the user community?
Are actual resource expenditures versus planned expenditures acceptable?
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TRANSITION PHASE
The transition phase is entered when a baseline is mature enough to be deployed in the end-user domain.
This typically requires that a usable subset of the system has been achieved with acceptable quality
levels and user documentation so that transition to the user will provide positive results. This phase
could include any of the following activities:
1. Beta testing to validate the new system against user expectations
2. Beta testing and parallel operation relative to a legacy system it is replacing
3. Conversion of operational databases
4. Training of users and maintainers
The transition phase concludes when the deployment baseline has achieved the complete vision.
PRIMARY OBJECTIVES
Achieving user self-supportability
Achieving stakeholder concurrence that deployment baselines are complete and consistent with
the evaluation criteria of the vision
Achieving final product baselines as rapidly and cost-effectively as practical
Synchronization and integration of concurrent construction increments into consistent
deployment baselines
Deployment-specific engineering (cutover, commercial packaging and production, sales
rollout kit development, field personnel training)
Assessment of deployment baselines against the complete vision and acceptance
criteria in the requirements set
EVALUATION CRITERIA
Is the usersatisfied?
Are actual resource expenditures versus planned expenditures acceptable?
Artifacts of the process
THE ARTIFACT SETS
To make the development of a complete software system manageable, distinct collections of information
are organized into artifact sets. Artifact represents cohesive information that typically is developed and
reviewed as a single entity.
Life-cycle software artifacts are organized into five distinct sets that are roughly partitioned by the
underlying language of the set: management (ad hoc textual formats), requirements (organized text and
models of the problem space), design (models of the solution space), implementation (human-readable
programming language and associated source files), and deployment (machine-process able languages and
associated files). The artifact sets are shown in Figure 6-1.
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THE MANAGEMENT SET
The management set captures the artifacts associated with process planning and execution. These
artifacts use ad hoc notations, including text, graphics, or whatever representation is required to
capture the "contracts" among project personnel (project management, architects, developers, testers,
marketers, administrators), among stakeholders (funding authority, user, software project manager,
organization manager, regulatory agency), and between project personnel and stakeholders. Specific
artifacts included in this set are the work breakdown structure (activity breakdown and financial
tracking mechanism), the business case (cost, schedule, profit expectations), the release
specifications (scope, plan, objectives for release baselines), the software development plan (project
process instance), the release descriptions (results of release baselines), the status assessments
(periodic snapshots of project progress), the software change orders (descriptions of discrete baseline
changes), the deployment documents (cutover plan, training course, sales rollout kit), and the
environment (hardware and software tools, process automation, & documentation).
Management set artifacts are evaluated, assessed, and measured through a combination of the following:
 Relevant stakeholder review
 Analysis of changes between the current version of the artifact and previous versions
 Major milestone demonstrations of the balance among all artifacts and, in particular, the
accuracy of the business case and vision artifacts
THE ENGINEERING SETS
The engineering sets consist of the requirements set, the design set, the implementation set, and
the deployment set.
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Requirements Set
Requirements artifacts are evaluated, assessed, and measured through a combination of the following:
 Analysis of consistency with the release specifications of the management set
 Analysis of consistency between the vision and the requirements models
 Mapping against the design, implementation, and deployment sets to evaluate the consistency
and completeness and the semantic balance between information in the different sets
 Analysis of changes between the current version of requirements artifacts and previous
versions (scrap, rework, and defect elimination trends)
 Subjective review of other dimensions of quality
Design Set
UML notation is used to engineer the design models for the solution. The design set contains
varying levels of abstraction that represent the components of the solution space (their identities,
attributes, static relationships, dynamic interactions). The design set is evaluated, assessed, and
measured through a combination of the following:
 Analysis of the internal consistency and quality of the design model
 Analysis of consistency with the requirements models
 Translation into implementation and deployment sets and notations (for example, traceability,
source code generation, compilation, linking) to evaluate the consistency and completeness and
the semantic balance between information in the sets
 Analysis of changes between the current version of the design model and previous versions
(scrap, rework, and defect elimination trends)
Implementation set
The implementation set includes source code (programming language notations) that represents the tangible
implementations of components (their form, interface, and dependency relationships)
Implementation sets are human-readable formats that are evaluated, assessed, and measured
through a combination of the following:
 Analysis of consistency with the design models
 Translation into deployment set notations (for example, compilation and linking) to evaluate the
consistency and completeness among artifact sets
 Assessment of component source or executable files against relevant evaluation criteria through
inspection, analysis, demonstration, or testing
 Execution of stand-alone component test cases that automatically compare expected results with
actual results
 Analysis of changes between the current version of the implementation set and previous
versions (scrap, rework, and defect elimination trends)
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Deployment Set
The deployment set includes user deliverables and machine language notations, executable software, and
the
build scripts, installation scripts, and executable target specific data necessary to use the product in its
target environment.
Deployment sets are evaluated, assessed, and measured through a combination of the following:
 Testing against the usage scenarios and quality attributes defined in the requirements set to
evaluate the consistency and completeness and the~ semantic balance between information in
the two sets
 Testing the partitioning, replication, and allocation strategies in mapping components of the
implementation set to physical resources of the deployment system (platform type, number,
network topology)
 Testing against the defined usage scenarios in the user manual such as installation, user-
orienteddynamic reconfiguration, mainstream usage, and anomaly management
 Analysis of changes between the current version of the deployment set and previous versions
(defect elimination trends, performance changes)
Each artifact set is the predominant development focus of one phase of the life cycle; the other sets take
on check and balance roles. As illustrated in Figure 6-2, each phase has a predominant focus:
Requirements are the focus of the inception phase; design, the elaboration phase; implementation, the
construction phase; and deployment, the transition phase. The management artifacts also evolve, but at a
fairly constant level across the life cycle.
Most of today's software development tools map closely to one of the five artifact sets.
1. Management: scheduling, workflow, defect tracking, change
management, documentation, spreadsheet, resource management, and
presentation tools
2. Requirements: requirements management tools
3. Design: visual modeling tools
4. Implementation: compiler/debugger tools, code analysis tools, test coverage analysis tools, and
test management tools
5. Deployment: test coverage and test automation tools, network management tools, commercial
components (operating systems, GUIs, RDBMS, networks, middleware), and installation tools.
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Implementation Set versus Deployment Set
The separation of the implementation set (source code) from the deployment set (executable code) is
important because there are very different concerns with each set. The structure of the information
delivered to the user (and typically the test organization) is very different from the structure of the source
code information. Engineering decisions that have an impact on the quality of the deployment set but are
relatively incomprehensible in the design and implementation sets include the following:
 Dynamically reconfigurable parameters (buffer sizes, color palettes, number of servers, number
of simultaneous clients, data files, run-time parameters)
 Effects of compiler/link optimizations (such as space optimization versus speed optimization)
 Performance under certain allocation strategies (centralized versus distributed, primary and
shadow threads, dynamic load balancing, hot backup versus checkpoint/rollback)Virtual
machine constraints (file descriptors, garbage collection, heap size, maximum record size, disk
file rotations)
 Process-level concurrency issues (deadlock and race conditions)
 Platform-specific differences in performance or behavior
ARTIFACT EVOLUTION OVER THE LIFE CYCLE
Each state of development represents a certain amount of precision in the final system description.
Early in the life cycle, precision is low and the representation is generally high. Eventually, the precision
of representation is high and everything is specified in full detail. Each phase of development focuses on a
particular artifact set. At the end of each phase, the overall system state will have progressed on all sets, as
illustrated in Figure 6-3.
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The inception phase focuses mainly on critical requirements usually with a secondary focus on an
initial deployment view. During the elaboration phase, there is much greater depth in requirements,
much more breadth in the design set, and further work on implementation and deployment issues. The
main focus of the construction phase is design and implementation. The main focus of the transition
phase is on achieving consistency and completeness of the deployment set in the context of the other
sets.
TEST ARTIFACTS
 The test artifacts must be developed concurrently with the product from inception through
deployment. Thus, testing is a full-life-cycle activity, not a late life-cycle activity.
 The test artifacts are communicated, engineered, and developed within the same artifact sets as
the developed product.
 The test artifacts are implemented in programmable and repeatable formats (as
software programs).
 The test artifacts are documented in the same way that the product is documented.
 Developers of the test artifacts use the same tools, techniques, and training as the
software engineers developing the product.
Test artifact subsets are highly project-specific, the following example clarifies the relationship between
test artifacts and the other artifact sets. Consider a project to perform seismic data processing for the
purpose of oil exploration. This system has three fundamental subsystems: (1) a sensor subsystem that
captures raw seismic data in real time and delivers these data to (2) a technical operations subsystem
that converts raw data into an organized database and manages queries to this database from (3) a
display subsystem that allows workstation operators to examine seismic data in human-readable form.
Such a system would result in the following test artifacts:
 Management set. The release specifications and release descriptions capture the objectives,
evaluation criteria, and results of an intermediate milestone. These artifacts are the test plans
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and test results negotiated among internal project teams. The software change orders capture
test results (defects, testability changes, requirements ambiguities, enhancements) and the
closure criteria associated with making a discrete change to a baseline.
 Requirements set. The system-level use cases capture the operational concept for the system
and the acceptance test case descriptions, including the expected behavior of the system and its
quality attributes. The entire requirement set is a test artifact because it is the basis of all
assessment activities across the life cycle.
 Design set. A test model for nondeliverable components needed to test the product baselines is
captured in the design set. These components include such design set artifacts as a seismic event
simulation for creating realistic sensor data; a "virtual operator" that can support unattended,
after- hours test cases; specific instrumentation suites for early demonstration of resource usage;
transaction rates or response times; and use case test drivers and component stand-alone test
drivers.
 Implementation set. Self-documenting source code representations for test components and test
drivers provide the equivalent of test procedures and test scripts. These source files may also
include human-readable data files representing certain statically defined data sets that are
explicit test source files. Output files from test drivers provide the equivalent of test reports.
 Deployment set. Executable versions of test components, test drivers, and data files are provided.
MANAGEMENT ARTIFACTS
The management set includes several artifacts that capture intermediate results and ancillary
information necessary to document the product/process legacy, maintain the product, improve the
product, and improve the process.
Business Case
The business case artifact provides all the information necessary to determine whether the project is
worth investing in. It details the expected revenue, expected cost, technical and management plans,
and backup data necessary to demonstrate the risks and realism of the plans. The main purpose is to
transform the vision into economic terms so that an organization can make an accurate ROI
assessment. The financial forecasts are evolutionary, updated with more accurate forecasts as the life
cycle progresses. Figure 6-4 provides a default outline for a business case.
Software Development Plan
The software development plan (SDP) elaborates the process framework into a fully detailed plan.
Two indications of a useful SDP are periodic updating (it is not stagnant shelfware) and
understanding and acceptance by managers and practitioners alike. Figure 6-5 provides a default
outline for a software development plan.
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Work Breakdown Structure
Work breakdown structure (WBS) is the vehicle for budgeting and collecting costs. To monitor and
control a project's financial performance, the software project man1ger must have insight into project
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costs and how they are expended. The structure of cost accountability is a serious project planning
constraint.
Software Change Order Database
Managing change is one of the fundamental primitives of an iterative development process. With greater
change freedom, a project can iterate more productively. This flexibility increases the content, quality,
and number of iterations that a project can achieve within a given schedule. Change freedom has been
achieved in practice through automation, and today's iterative development environments carry the
burden of change management. Organizational processes that depend on manual change management
techniques have encountered major inefficiencies.
Release Specifications
The scope, plan, and objective evaluation criteria for each baseline release are derived from the vision
statement as well as many other sources (make/buy analyses, risk management concerns, architectural
considerations, shots in the dark, implementation constraints, quality thresholds). These artifacts are
intended to evolve along with the process, achieving greater fidelity as the life cycle progresses and
requirements understanding matures. Figure 6-6 provides a default outline for a release specification
Release Descriptions
Release description documents describe the results of each release, including performance against each
of the evaluation criteria in the corresponding release specification. Release baselines should be
accompanied by a release description document that describes the evaluation criteria for that
configuration baseline and provides substantiation (through demonstration, testing, inspection, or
analysis) that each criterion has been addressed in an acceptable manner. Figure 6-7 provides a default
outline for a release description.
Status Assessments
Status assessments provide periodic snapshots of project health and status, including the software project
manager's risk assessment, quality indicators, and management indicators. Typical status assessments
should include a review of resources, personnel staffing, financial data (cost and revenue), top 10 risks,
technical progress (metrics snapshots), major milestone plans and results, total project or product scope &
action items
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Environment
An important emphasis of a modern approach is to define the development and maintenance environment
as a first-class artifact of the process. A robust, integrated development environment must support
automation of the development process. This environment should include requirements management,
visual modeling, document automation, host and target programming tools, automated regression testing,
and continuous and integrated change management, and feature and defect tracking.
Deployment
A deployment document can take many forms. Depending on the project, it could include several
document subsets for transitioning the product into operational status. In big contractual efforts in which
the system is delivered to a separate maintenance organization, deployment artifacts may include
computer system operations manuals, software installation manuals, plans and procedures for cutover
(from a legacy system), site surveys, and so forth. For commercial software products, deployment artifacts
may include marketing plans, sales rollout kits, and training courses.
Management Artifact Sequences
In each phase of the life cycle, new artifacts are produced and previously developed artifacts are updated
to incorporate lessons learned and to capture further depth and breadth of the solution. Figure 6-8
identifies a typical sequence of artifacts across the life-cycle phases.
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ENGINEERING ARTIFACTS
Most of the engineering artifacts are captured in rigorous engineering notations such as UML,
programming languages, or executable machine codes. Three engineering artifacts are explicitly
intended for more general review, and they deserve further elaboration.
Vision Document
The vision document provides a complete vision for the software system under development and.
supports the contract between the funding authority and the development organization. A project
vision is meant to be changeable as understanding evolves of the requirements, architecture, plans,
and technology. A good vision document should change slowly. Figure 6-9 provides a default outline
for a vision document.
Architecture Description
The architecture description provides an organized view of the software architecture under
development. It is extracted largely from the design model and includes views of the design,
implementation, and deployment sets sufficient to understand how the operational concept of the
requirements set will be achieved. The breadth of the architecture description will vary from project
to project depending on many factors. Figure 6-10 provides a default outline for an architecture
description.
Model based software architecture
ARCHITECTURE: A MANAGEMENT PERSPECTIVE
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The most critical technical product of a software project is its architecture: the infrastructure,
control, and data interfaces that permit software components to cooperate as a system and
software designers to cooperate efficiently as a team. When the communications media
include multiple languages and intergroup literacy varies, the communications problem can
become extremely complex and even unsolvable. If a software development team is to be
successful, the inter project communications, as captured in the software architecture, must
be both accurate and precise
From a management perspective, there are three different aspects of architecture.
1. An architecture (the intangible design concept) is the design of a software system
this includes all engineering necessary to specify a complete bill of materials.
2. An architecture baseline (the tangible artifacts) is a slice of information across the
engineering artifact sets sufficient to satisfy all stakeholders that the vision
(function and quality) can be achieved within the parameters of the business case
(cost, profit, time, technology, and people).
3. An architecture description (a human-readable representation of an architecture,
which is one of the components of an architecture baseline) is an organized subset
of information extracted from the design set model(s). The architecture
description communicates how the intangible concept is realized in the tangible
artifacts.
The number of views and the level of detail in each view can vary widely.
The importance of software architecture and its close linkage with modern software
development processes can be summarized as follows:
 Achieving a stable software architecture represents a significant project milestone
at which the critical make/buy decisions should have been resolved.
 Architecture representations provide a basis for balancing the trade-offs between
the problem space (requirements and constraints) and the solution space (the
operational product).
 The architecture and process encapsulate many of the important (high-payoff or
high-risk) communications among individuals, teams, organizations, and
stakeholders.
 Poor architectures and immature processes are often given as reasons for project
failures.
 A mature process, an understanding of the primary requirements, and a
demonstrable architecture are important prerequisites for predictable planning.
 Architecture development and process definition are the intellectual steps that map
the problem to a solution without violating the constraints; they require human
innovation and cannot be automated.
ARCHITECTURE: A TECHNICAL PERSPECTIVE
An architecture framework is defined in terms of views that are abstractions of the UML
models in the design set. The design model includes the full breadth and depth of information.
An architecture view is an abstraction of the design model; it contains only the
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architecturally significant information. Most real-world systems require four views: design,
process, component, and deployment. The purposes of these views are as follows:
 Design: describes architecturally significant structures and functions of the design
model
 Process: describes concurrency and control thread relationships among the design,
component, and deployment views
 Component: describes the structure of the implementation set
 Deployment: describes the structure of the deployment set
Figure 7-1 summarizes the artifacts of the design set, including the architecture views and
architecture description.
The requirements model addresses the behavior of the system as seen by its end users,
analysts, and testers. This view is modeled statically using use case and class diagrams, and
dynamically using sequence, collaboration, state chart, and activity diagrams.
 The use case view describes how the system's critical (architecturally significant)
use cases are realized by elements of the design model. It is modeled statically
using use case diagrams, and dynamically using any of the UML behavioral
diagrams.
 The design view describes the architecturally significant elements of the design
model. This view, an abstraction of the design model, addresses the basic structure
and functionality of the solution. It is modeled statically using class and object
diagrams, and dynamically using any of the UML behavioral diagrams.
 The process view addresses the run-time collaboration issues involved in executing
the architecture on a distributed deployment model, including the logical software
network topology (allocation to processes and threads of control), interprocess
communication, and state management. This view is modeled statically using
deployment diagrams, and dynamically using any of the UML behavioral
diagrams.
 The component view describes the architecturally significant elements of the
implementation set. This view, an abstraction of the design model, addresses the
software source code realization of the system from the perspective of the project's
integrators and developers, especially with regard to releases and configuration
management. It is modeled statically using component diagrams, and dynamically
using any of the UML behavioral diagrams.
 The deployment view addresses the executable realization of the system, including
the allocation of logical processes in the distribution view (the logical software
topology) to physical resources of the deployment network (the physical system
topology). It is modeled statically using deployment diagrams, and dynamically
using any of the UML behavioral diagrams.
Generally, an architecture baseline should include the following:
 Requirements: critical use cases, system-level quality objectives, and priority
relationships among features and qualities
 Design: names, attributes, structures, behaviors, groupings, and relationships of
significant classes and components
 Implementation: source component inventory and bill of materials (number, name,
purpose, cost) of all primitive components
 Deployment: executable components sufficient to demonstrate the critical use
cases and the risk associated with achieving the system qualities
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Software User Manual
The software user manual provides the user with the reference documentation necessary to support
the delivered software. Although content is highly variable across application domains, the user
manual should include installation procedures, usage procedures and guidance, operational
constraints, and a user interface description, at a minimum. For software products with a user
interface, this manual should be developed early in the life cycle because it is a necessary
mechanism for communicating and stabilizing an important subset of requirements. The user manual
should be written by members of the test team, who are more likely to understand the user's
perspective than the development team.
PRAGMATIC ARTIFACTS
People want to review information but don't understand the language of the artifact. Many
interested reviewers of a particular artifact will resist having to learn the engineering language in
which the artifact is written. It is not uncommon to find people (such as veteran software managers,
veteran quality assurance specialists, or an auditing authority from a regulatory agency) who react as
follows: "I'm not going to learn UML, but I want to review the design of this software, so give me a
separate description such as some flowcharts and text that I can understand."
People want to review the information but don't have access to the tools. It is not very common
for the development organization to be fully tooled; it is extremely rare that the/other stakeholders
have any capability to review the engineering artifacts on-line. Consequently, organizations are
forced to exchange paper documents. Standardized formats (such as UML, spreadsheets, Visual
Basic, C++, and Ada 95), visualization tools, and the Web are rapidly making it economically
feasible for all stakeholders to exchange
information electronically.
Human-readable engineering artifacts should use rigorous notations that are complete,
consistent, and used in a self-documenting manner. Properly spelled English words should be
used for all identifiers and descriptions. Acronyms and abbreviations should be used only where they
are well accepted jargon in the context of the component's usage. Readability should be emphasized
and the use of proper English words should be required in all engineering artifacts. This practice
enables understandable representations, browse able formats (paperless review), more-rigorous
notations, and reduced error rates.
Useful documentation is self-defining: It is documentation that gets used.
Paper is tangible; electronic artifacts are too easy to change. On-line and Web-based artifacts
can be changed easily and are viewed with more skepticism because of their inherent volatility.
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UNIT III
Workflows and Checkpoints of process
Workflow of the process
SOFTWARE PROCESS WORKFLOWS
The term WORKFLOWS is used to mean a thread of cohesive and mostly sequential activi-
ties. Workflows are mapped to product artifacts There are seven top-level workflows:
1. Management workflow: controlling the process and ensuring win conditions for all
stakeholders
2. Environment workflow: automating the process and evolving the maintenance
environment
3. Requirements workflow: analyzing the problem space and evolving the
requirements artifacts
4. Design workflow: modeling the solution and evolving the architecture and design
artifacts
5. Implementation workflow: programming the components and evolving the
implementation and deployment artifacts
6. Assessment workflow: assessing the trends in process and product quality
7. Deployment workflow: transitioning the end products to the user
Figure 8-1 illustrates the relative levels of effort expected across the phases in each of the top-
level workflows.
Table 8-1 shows the allocation of artifacts and the emphasis of each workflow in each of the
life-cycle phases of inception, elaboration, construction, and transition.
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ITERATION WORKFLOWS
Iteration consists of a loosely sequential set of activities in various proportions, depending on
where the iteration is located in the development cycle. Each iteration is defined in terms of a
set of allocated usage scenarios. An individual iteration's workflow, illustrated in Figure 8-2,
generally includes the following sequence:
 Management: iteration planning to determine the content of the release and develop
the detailed plan for the iteration; assignment of work packages, or tasks, to the
development team
 Environment: evolving the software change order database to reflect all new
baselines and changes to existing baselines for all product, test, and environment
components
 Requirements: analyzing the baseline plan, the baseline architecture, and the
baseline requirements set artifacts to fully elaborate the use cases to be
demonstrated at the end of this iteration and their evaluation criteria; updating any
requirements set artifacts to reflect changes necessitated by results of this
iteration's engineering activities
 Design: evolving the baseline architecture and the baseline design set artifacts to
elaborate fully the design model and test model components necessary to
demonstrate against the evaluation criteria allocated to this iteration; updating
design set artifacts to reflect changes necessitated by the results of this iteration's
engineering activities
 Implementation: developing or acquiring any new components, and enhancing or
modifying any existing components, to demonstrate the evaluation criteria
allocated to this iteration; integrating and testing all new and modified components
with existing baselines (previous versions)
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 Assessment: evaluating the results of the iteration, including compliance with the
allocated evaluation criteria and the quality of the current baselines; identifying
any rework required and determining whether it should be performed before
deployment of this release or allocated to the next release; assessing results to
improve the basis of the subsequent iteration's plan
 Deployment: transitioning the release either to an external organization (such as a
user, independent verification and validation contractor, or regulatory agency) or
to internal closure by conducting a post-mortem so that lessons learned can be
captured and reflected in the next iteration
Iterations in the inception and elaboration phases focus on management. Requirements, and
design activities. Iterations in the construction phase focus on design, implementation, and
assessment. Iterations in the transition phase focus on assessment and deployment. Figure 8-
3 shows the emphasis on different activities across the life cycle. An iteration represents the
state of the overall architecture and the complete deliverable system. An increment
represents the current progress that will be combined with the preceding iteration to from the
next iteration. Figure 8-4, an example of a simple development life cycle, illustrates the
differences between iterations and increments.
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8. Checkpoints of the process
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Three types of joint management reviews are conducted throughout the process:
1. Major milestones. These system wide events are held at the end of each
development phase. They provide visibility to system wide issues, synchronize the
management and engineering perspectives, and verify that the aims of the phase
have been achieved.
2. Minor milestones. These iteration-focused events are conducted to review the
content of an iteration in detail and to authorize continued work.
3. Status assessments. These periodic events provide management with frequent and
regular insight into the progress being made.
Each of the four phases-inception, elaboration, construction, and transition consists of one or
more iterations and concludes with a major milestone when a planned technical capability is
produced in demonstrable form. An iteration represents a cycle of activities for which there is
a well-defined intermediate result-a minor milestone-captured with two artifacts: a release
specification (the evaluation criteria and plan) and a release description (the results). Major
milestones at the end of each phase use formal, stakeholder-approved evaluation criteria and
release descriptions; minor milestones use informal, development-team-controlled versions of
these artifacts.
Figure 9-1 illustrates a typical sequence of project checkpoints for a relatively large project.
MAJOR MILESTONES
The four major milestones occur at the transition points between life-cycle phases. They can
be used in many different process models, including the conventional waterfall model. In an
iterative model, the major milestones are used to achieve concurrence among all stakeholders
on the current state of the project. Different stakeholders have very different concerns:
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 Customers: schedule and budget estimates, feasibility, risk assessment,
requirements understanding, progress, product line compatibility
 Users: consistency with requirements and usage scenarios, potential for
accommodating growth, quality attributes
 Architects and systems engineers: product line compatibility, requirements changes,
trade-off analyses, completeness and consistency, balance among risk, quality, and
usability
 Developers: sufficiency of requirements detail and usage scenario descriptions, .
frameworks for component selection or development, resolution of development
risk, product line compatibility, sufficiency of the development environment
 Maintainers: sufficiency of product and documentation artifacts, understandability,
interoperability with existing systems, sufficiency of maintenance environment
 Others: possibly many other perspectives by stakeholders such as regulatory
agencies, independent verification and validation contractors, venture capital
investors, subcontractors, associate contractors, and sales and marketing teams
Table 9-1 summarizes the balance of information across the major milestones.
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Life-Cycle Objectives Milestone
The life-cycle objectives milestone occurs at the end of the inception phase. The goal is to
present to all stakeholders a recommendation on how to proceed with development, including
a plan, estimated cost and schedule, and expected benefits and cost savings. A successfully
completed life-cycle objectives milestone will result in authorization from all stakeholders to
proceed with the elaboration phase.
Life-Cycle Architecture Milestone
The life-cycle architecture milestone occurs at the end of the elaboration phase. The primary
goal is to demonstrate an executable architecture to all stakeholders. The baseline architecture
consists of both a human-readable representation (the architecture document) and a
configuration-controlled set of software components captured in the engineering artifacts. A
successfully completed life-cycle architecture milestone will result in authorization from the
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stakeholders to proceed with the construction phase.
The technical data listed in Figure 9-2 should have been reviewed by the time of the lifecycle
architecture milestone. Figure 9-3 provides default agendas for this milestone.
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Initial Operational Capability Milestone
The initial operational capability milestone occurs late in the construction phase. The goals
are to assess the readiness of the software to begin the transition into customer/user sites and
to authorize the start of acceptance testing. Acceptance testing can be done incrementally
across multiple iterations or can be completed entirely during the transition phase is not
necessarily the completion of the construction phase.
Product Release Milestone
The product release milestone occurs at the end of the transition phase. The goal is to assess
the completion of the software and its transition to the support organization, if any. The
results of acceptance testing are reviewed, and all open issues are addressed. Software
quality metrics are reviewed to determine whether quality is sufficient for transition to the
support organization.
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MINOR MILESTONES
For most iterations, which have a one-month to six-month duration, only two minor
milestones are needed: the iteration readiness review and the iteration assessment review.
 Iteration Readiness Review. This informal milestone is conducted at the start of
each iteration to review the detailed iteration plan and the evaluation criteria that
have been allocated to this iteration .
 Iteration Assessment Review. This informal milestone is conducted at the end of
each iteration to assess the degree to which the iteration achieved its objectives
and satisfied its evaluation criteria, to review iteration results, to review
qualification test results (if part of the iteration), to determine the amount of
rework to be done, and to review the impact of the iteration results on the plan for
subsequent iterations.
The format and content of these minor milestones tend to be highly dependent on the project
and the organizational culture. Figure 9-4 identifies the various minor milestones to be
considered when a project is being planned.
PERIODIC STATUS ASSESSMENTS
Periodic status assessments are management reviews conducted at regular intervals
(monthly, quarterly) to address progress and quality indicators, ensure continuous attentionto
project dynamics, and maintain open communications among all stakeholders.
Periodic status assessments serve as project snapshots. While the period may vary, the
recurring event forces the project history to be captured and documented. Status assessments
provide the following:
 A mechanism for openly addressing, communicating, and resolving management
issues, technical issues, and project risks
 Objective data derived directly from on-going activities and evolving product
configurations
 A mechanism for disseminating process, progress, quality trends, practices, and
experience information to and from all stakeholders in an open forum
Periodic status assessments are crucial for focusing continuous attention on the evolving
health of the project and its dynamic priorities. They force the software project manager to
collect and review the data periodically, force outside peer review, and encourage
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dissemination of best practices to and from other stakeholders.
The default content of periodic status assessments should include the topics identified in Table
9-2.
process planning
A good work breakdown structure and its synchronization with the process framework are critical
factors in software project success. Development of a work breakdown structure dependent on the
project management style, organizational culture, customer preference, financial constraints, and
several other hard-to-define, project-specific parameters.
A WBS is simply a hierarchy of elements that decomposes the project plan into the discrete
work tasks. A WBS provides the following information structure:
 A delineation of all significant work
 A clear task decomposition for assignment of responsibilities
 A framework for scheduling, budgeting, and expenditure tracking
Many parameters can drive the decomposition of work into discrete tasks: product
subsystems, components, functions, organizational units, life-cycle phases, even geographies.
Most systems have a first-level decomposition by subsystem. Subsystems are then
decomposed into their components, one of which is typically the software.
CONVENTIONAL WBS ISSUES
Conventional work breakdown structures frequently suffer from three fundamental flaws.
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1. They are prematurely structured around the product design.
2. They are prematurely decomposed, planned, and budgeted in either too much or
too little detail.
3. They are project-specific, and cross-project comparisons are usually difficult or
impossible.
Conventional work breakdown structures are prematurely structured around the product
design. Figure 10-1 shows a typical conventional WBS that has been structured primarily
around the subsystems of its product architecture, then further decomposed into the
components of each subsystem. A WBS is the architecture for the financial plan.
Conventional work breakdown structures are prematurely decomposed, planned, and
budgeted in either too little or too much detail. Large software projects tend to be over
planned and small projects tend to be under planned. The basic problem with planning too
much detail at the outset is that the detail does not evolve with the level of fidelity in the
plan.
Conventional work breakdown structures are project-specific, and cross-project comparisons are usually
difficult or impossible. With no standard WBS structure, it is extremely difficult to compare plans, financial data,
schedule data, organizational efficiencies, cost trends, productivity trends, or quality trends across multiple projects.
Figure 10-1 Conventional work breakdown structure, following the product hierarchy
Management
System requirement and design
Subsystem 1
Component 11
Requirements
Design
Code
Test
Documentation
…(similar structures for other components)
Component 1N
Requirements
Design
Code
Test
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Documentation
…(similar structures for other subsystems)
Subsystem M
Component M1
Requirements
Design
Code
Test
Documentation
…(similar structures for other components)
Component MN
Requirements
Design
Code
Test
Documentation
Integration and test
Test planning
Test procedure preparation
Testing
Test reports
Other support areas
Configuration control
Quality assurance
System administration
EVOLUTIONARY WORK BREAKDOWN STRUCTURES
An evolutionary WBS should organize the planning elements around the process framework
rather than the product framework. The basic recommendation for the WBS is to organize
the hierarchy as follows:
 First-level WBS elements are the workflows (management, environment,
requirements, design, implementation, assessment, and deployment).
 Second-level elements are defined for each phase of the life cycle (inception,
elaboration, construction, and transition).
 Third-level elements are defined for the focus of activities that produce the artifacts
of each phase.
A default WBS consistent with the process framework (phases, workflows, and artifacts)
is shown in Figure 10-2. This recommended structure provides one example of how the
elements of the process framework can be integrated into a plan. It provides a
framework for estimating the costs and schedules of each element, allocating them
across a project organization, and tracking expenditures.
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The structure shown is intended to be merely a starting point. It needs to be tailored to
the specifics of a project in many ways.
 Scale. Larger projects will have more levels and substructures.
 Organizational structure. Projects that include subcontractors or span multiple
organizational entities may introduce constraints that necessitate different WBS
allocations.
 Degree of custom development. Depending on the character of the project, there
can be very different emphases in the requirements, design, and implementation
workflows.
 Business context. Projects developing commercial products for delivery to a broad
customer base may require much more elaborate substructures for the deployment
element.
 Precedent experience. Very few projects start with a clean slate. Most of them are
developed as new generations of a legacy system (with a mature WBS) or in the
context of existing organizational standards (with preordained WBS expectations).
The WBS decomposes the character of the project and maps it to the life cycle, the
budget, and the personnel. Reviewing a WBS provides insight into the important
attributes, priorities, and structure of the project plan.
Another important attribute of a good WBS is that the planning fidelity inherent in each
element is commensurate with the current life-cycle phase and project state. Figure 10-3
illustrates this idea. One of the primary reasons for organizing the default WBS the way I
have is to allow for planning elements that range from planning packages (rough budgets that
are maintained as an estimate for future elaboration rather than being decomposed into
detail) through fully planned activity networks (with a well-defined budget and continuous
assessment of actual versus planned expenditures).
Figure 10-2 Default work breakdownstructure A
Management
AA Inception phase management AAA
Business case development
AAB Elaboration phase release specifications AAC
Elaboration phase WBS specifications AAD
Software development plan
AAE Inception phase project control and statusassessments AB
Elaboration phase management
ABA Construction phase release specifications ABB
Construction phase WBS baselining
ABC Elaboration phase project control and status assessments
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AC Construction phase management ACA
Deployment phase planning
ACB Deployment phase WBS baselining
ACC Construction phase project control and statusassessments AD
Transition phase management
ADA Next generation planning
ADB Transition phase project control and statusassessments B
Environment
BA Inception phase environment specification BB
Elaboration phase environment baselining
BBA Development environment installation and administration BBB
Development environment integration and customtoolsmithing BBC
SCO database formulation
BC Construction phase environment maintenance
BCA Development environment installation and administration BCB
SCO database maintenance
BD Transition phase environment maintenance
BDA Development environment maintenance and administration BDB
SCO database maintenance
BDC Maintenance environment packaging and transition C
Requirements
CA Inception phase requirementsdevelopment CCA
Vision specification
CAB Use case modeling
CB Elaboration phase requirements baselining CBA
Vision baselining
CBB Use case model baselining
CC Construction phase requirements maintenance CD
Transition phase requirements maintenance
D Design
DA Inception phase architecture prototyping DB
Elaboration phase architecture baselining DBA
Architecture design modeling
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DBB Design demonstration planning and conduct DBC
Software architecture description
DC Construction phase design modeling
DCA Architecture design model maintenance DCB
Component design modeling
DD Transition phase design maintenance E
Implementation
EA Inception phase component prototyping
EB Elaboration phase component implementation
EBA Critical component coding demonstration integration
EC Construction phase component implementation
ECA Initial release(s) component coding and stand-alonetesting ECB
Alpha release component coding and stand-alone testing ECC Beta
release component coding and stand-alone testing
ECD Component maintenance F
Assessment
FA Inception phase assessment FB
Elaboration phase assessment
FBA Test modeling
FBB Architecture test scenario implementation
FBC Demonstration assessment and releasedescriptions FC
Construction phase assessment
FCA Initial release assessment and release description FCB
Alpha release assessment and release description FCC Beta
release assessment and release description
FD Transition phase assessment
FDA Product release assessment and release description G
Deployment
GA Inception phase deployment planning GB
Elaboration phase deployment planning GC
Construction phase deployment
GCA User manual baselining GD
Transition phase deployment
GDA Product transition to user
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Figure 10-3 Evolution of planning fidelity in the WBS over the life cycle
Inception Elaboration
WBS Element Fidelity Management High
Environment Moderate
Requirement High
Design Moderate Implementation Low Assessment Low
Deployment Low
WBS Element Fidelity Management High
Environment High
Requirement High
Design High Implementation Moderate Assessment
Moderate
Deployment Low
WBS Element
Management
Fidelity
High
WBS Element
Management
Fidelity
High
Environment High Environment High
Requirements Low Requirements Low
Design Low Design Moderate
Implementation Moderate Implementation High
Assessment High Assessment High
Deployment High Deployment Moderate
Transition Construction
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PLANNING GUIDELINES
Software projects span a broad range of application domains. It is valuable but risky to make
specific planning recommendations independent of project context. Project-independent
planning advice is also risky. There is the risk that the guidelines may pe adopted blindly
without being adapted to specific project circumstances. Two simple planning guidelines
should be considered when a project plan is being initiated or assessed. The first guideline,
detailed in Table 10-1, prescribes a default allocation of costs among the first-level WBS
elements. The second guideline, detailed in Table 10-2, prescribes the allocation of effort and
schedule across the lifecycle phases.
10-1 Web budgeting defaults
First Level WBS Element Default Budget
Management 10%
Environment 10%
Requirement 10%
Design 15%
Implementation 25%
Assessment 25%
Deployment 5%
Total 100%
Table 10-2 Default distributions of effort and schedule by phase
Effort 5% 20% 65% 10%
Schedule 10% 30% 50% 10%
THE COST AND SCHEDULE ESTIMATING PROCESS
Project plans need to be derived from two perspectives. The first is a forward-looking, top-
down approach. It starts with an understanding of the general requirements and constraints,
derives a macro-level budget and schedule, then decomposes these elements into lower level
budgets and intermediate milestones. From this perspective, the following planning sequence
would occur:
1. The software project manager (and others) develops a characterization of the overall
size, process, environment, people, and quality required for the project.
2. A macro-level estimate of the total effort and schedule is developed using a
software cost estimation model.
3. The software project manager partitions the estimate for the effort into a top-level
WBS using guidelines such as those in Table 10-1.
4. At this point, subproject managers are given the responsibility for decomposing
each of the WBS elements into lower levels using their top-level allocation, staffing
profile, and major milestone dates as constraints.
Domain Inception Elaboration Constructio
n
Transition
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The second perspective is a backward-looking, bottom-up approach. We start with the end in
mind, analyze the micro-level budgets and schedules, then sum all these elements into the
higher level budgets and intermediate milestones. This approach tends to define and
populate the WBS from the lowest levels upward. From this perspective, the following
planning sequence would occur:
1. The lowest level WBS elements are elaborated into detailed tasks
2. Estimates are combined and integrated into higher level budgets and milestones.
3. Comparisons are made with the top-down budgets and schedule milestones.
Milestone scheduling or budget allocation through top-down estimating tends to exaggerate
the project management biases and usually results in an overly optimistic plan. Bottom-up
estimates usually exaggerate the performer biases and result in an overly pessimistic plan.
These two planning approaches should be used together, in balance, throughout the life
cycle of the project. During the engineering stage, the top-down perspective will dominate
because there is usually not enough depth of understanding nor stability in the detailed task
sequences to perform credible bottom-up planning. During the production stage, there should
be enough precedent experience and planning fidelity that the bottom-up planning
perspective will dominate. Top-down approach should be well tuned to the project-specific
parameters, so it should be used more as a global assessment technique. Figure 10-4
illustrates this life-cycle planning balance.
Figure 10-4 Planning balance throughout the life cycle
Bottom up task level planning based on metrics
from previous iteration
Top down project level planning based on microanalysis from
previous projects
Engineering Stage Production Stage
Inception Elaboration Construction Transition
Feasibility iteration Architecture iteration Usable iteration Product
Releases
Engineering stage planning
emphasis
Production stage planning
emphasis
Macro level task estimation for
production stage artifacts
Micro level task estimation for
production stage artifacts
Micro level task estimation for
engineering artifacts
Macro level task estimation for
maintenance of engineering artifacts
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Stakeholder concurrence Stakeholder concurrence
Coarse grained variance analysis of
actual vs planned expenditures
Fine grained variance analysis of actual
vs planned expenditures
Tuning the top down project
independent planning guidelines into
project specific planning guidelines
WBS definition and elaboration
THE ITERATION PLANNING PROCESS
Planning is concerned with defining the actual sequence of intermediate results. An
evolutionary build plan is important because there are always adjustments in build content
and schedule as early conjecture evolves into well-understood project circumstances.
Iteration is used to mean a complete synchronization across the project, with a well-
orchestrated global assessment of the entire project baseline.
 Inception iterations. The early prototyping activities integrate the foundation
components of a candidate architecture and provide an executable framework for
elaborating the critical use cases of the system. This framework includes existing
components, commercial components, and custom prototypes sufficient to
demonstrate a candidate architecture and sufficient requirements understanding to
establish a credible business case, vision, and software development plan.
 Elaboration iterations. These iterations result in architecture, including a complete
framework and infrastructure for execution. Upon completion of the architecture
iteration, a few critical use cases should be demonstrable: (1) initializing the architecture,
(2) injecting a scenario to drive the worst-case data processing flow through the system
(for example, the peak transaction throughput or peak load scenario), and (3) injecting a
scenario to drive the worst-case control flow through the system (for example,
orchestrating the fault-tolerance use cases).
 Construction iterations. Most projects require at least two major construction iterations:
an alpha release and a beta release.
 Transition iterations. Most projects use a single iteration to transition a beta release into
the final product.
The general guideline is that most projects will use between four and nine iterations. The typical project
would have the following six-iteration profile:
 One iteration in inception: an architecture prototype
 Two iterations in elaboration: architecture prototype and architecture baseline
 Two iterations in construction: alpha and beta releases
 One iteration in transition: product release
A very large or unprecedented project with many stakeholders may require additional
inception iteration and two additional iterations in construction, for a total of nine iterations.
PRAGMATIC PLANNING
Even though good planning is more dynamic in an iterative process, doing it accurately is far
easier. While executing iteration N of any phase, the software project manager must be
monitoring and controlling against a plan that was initiated in iteration N - 1 and must be
planning iteration N + 1. The art of good project· management is to make trade-offs in the
current iteration plan and the next iteration plan based on objective results in the current
iteration and previous iterations. Aside from bad architectures and misunderstood
requirements, inadequate planning (and subsequent bad management) is one of the most
common reasons for project failures. Conversely, the success of every successful project can
be attributed in part to good planning.
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A project's plan is a definition of how the project requirements will be transformed into' a
product within the business constraints. It must be realistic, it must be current, it must be a
team product, it must be understood by the stakeholders, and it must be used. Plans are not
just for managers. The more open and visible the planning process and results, the more
ownership there is among the team members who need to execute it. Bad, closely held plans
cause attrition. Good, open plans can shape cultures and encourage teamwork.
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UNIT IV
Project Organizations
Project Organizations and Responsibilities:
 Organizations engaged in software Line-of-Business need to support projects with
the infrastructure necessary to use a common process.
 Project organizations need to allocate artifacts & responsibilities across project team
to ensure a balance of global (architecture) & local (component) concerns.
 The organization must evolve with the WBS & Life cycle concerns.
 Software lines of business & product teams have different motivation.
 Software lines of business are motivated by return of investment (ROI),new
business discriminators, market diversification & profitability.
 Project teams are motivated by the cost, Schedule & quality of specific deliverables
1) Line-Of-Business Organizations:
The main features of default organization are as follows:
• Responsibility for process definition & maintenance is specific to a cohesive line
of business.
• Responsibility for process automation is an organizational role & is equal in
importance to the process definition role.
• Organizational role may be fulfilled by a single individual or several different
teams.
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Fig: Default roles in a software Line-of-Business Organization.
Software Engineering Process Authority (SEPA)
The SEPA facilities the exchange of information & process guidance both to & from
project practitioners
This role is accountable to General Manager for maintaining a current
assessment of the organization9s process maturity & its plan for future improvement
Project Review Authority (PRA)
The PRA is the single individual responsible for ensuring that a software project
complies with all organizational & business unit software policies, practices & standards
A software Project Manager is responsible for meeting the requirements of a contract or some
other project compliance standard
Software Engineering Environment Authority( SEEA )
The SEEA is responsible for automating the organization9s process, maintaining the
organization9s standard environment, Training projects to use the environment & maintaining
organization-wide reusable assets
The SEEA role is necessary to achieve a significant ROI for common process.
Infrastructure
An organization9s infrastructure provides human resources support, project-
independent research & development, & other capital software engineering assets.
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2) Project organizations:
• The above figure shows a default project organization and maps project-level roles
and responsibilities.
• The main features of the default organization are as follows:
• The project management team is an active participant, responsible for producing as
well as managing.
• The architecture team is responsible for real artifacts and for the integration of
components, not just for staff functions.
• The development team owns the component construction and maintenance activities.
• The assessment team is separate from development.
• Quality is everyone9s into all activities and checkpoints.
• Each team takes responsibility for a different quality perspective.
Figure11-2.Defaultprojectorganization andresponsibilities
Software Assessment
Software Development
Software Architecture
Administration
System engineering
Customerinterface,PRA interface
Planning, monitoring
Risk management
Softwareprocessdefinition
Process improvement
 Business case
 Softwaredevelopmentplan
 Status assessments
Software Management
Artifacts Activities
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3) EVOLUTION OF ORGANIZATIONS:
Software
Management
10%
Software
Assessment
20%
Inception
Transition
Elaboration
Construction
Software
Assessment
30%
Inception:
Software management: 50%
Software Architecture: 20%
Software development: 20%
Software Assessment
(measurement/evaluation):10%
Elaboration:
Software Assessment
Construction:
Software Assessment
Transition:
Software Assessment
Introductory Remarks:
The Process Automation:
Software
Management
10%
Software
Architecture
5%
Software
Development
35%
Software
Assessment
50% Software
Architecture
10%
Software
Management
50%
Software
Management
10%
Software
Developmen
t 50%
Software
Developmen
t 20%
Software
Architecture
50%
Software
Architectur
e 20%
Software
Developme
nt 20%
Software
Assessme
nt 10%
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The environment must be the first-class artifact of the process.
Process automation & change management is critical to an iterative process. If the change is
expensive then the development organization will resist it.
Round-trip engineering & integrated environments promote change freedom & effective
evolution of technical artifacts.
Metric automation is crucial to effective project control.
External stakeholders need access to environment resources to improve interaction with the
development team & add value to the process.
The three levels of process which requires a certain degree of process automation for the
corresponding process to be carried out efficiently.
Metaprocess (Line of business): The automation support for this level is called an
infrastructure.
Macroproces (project): The automation support for a project9s process is called an
environment.
Microprocess (iteration): The automation support for generating artifacts is generally called
a tool.
Tools: Automation Building blocks:
Many tools are available to automate the software development process. Most of the
core software development tools map closely to one of the process workflows
Workflows Environment Tools & process Automation
Management Workflow automation, Metrics automation
Environment Change Management, Document Automation
Requirements Requirement Management
Design Visual Modeling
Implementation -Editors, Compilers, Debugger, Linker, Runtime
Assessment -Test automation, defect Tracking
Deployment defect Tracking
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PROCESS AUTOMATION
The Project Environment:
The project environment artifacts evolve through three discrete states.
(1)Prototyping Environment.(2)Development Environment.(3)Maintenance Environment.
The Prototype Environment includes an architecture test bed for prototyping project
architecture to evaluate trade-offs during inception & elaboration phase of the life cycle.
The Development environment should include a full suite of development tools needed to support various
Process workflows & round-trip engineering to the maximum extent possible.
The Maintenance Environment should typically coincide with the mature version of the
development.
There are four important environment disciplines that are critical to management context &
the success of a modern iterative development process.
Round-Trip engineering
Change Management
Software Change Orders (SCO)
Configuration baseline Configuration Control Board
Infrastructure
Organization Policy
Organization Environment
Stakeholder Environment.
Round Trip Environment
Tools must be integrated to maintain consistency & traceability.
Round-Trip engineering is the term used to describe this key requirement for environment
that support iterative development.
As the software industry moves into maintaining different information sets for the
engineering artifacts, more automation support is needed to ensure efficient & error free
transition of data from one artifacts to another.
Round-trip engineering is the environment support necessary to maintain Consistency among
the engineering artifacts.
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Change Management
Change management must be automated & enforced to manage multiple iterations & to
enable change freedom.
Change is the fundamental primitive of iterative Development.
I. Software Change Orders
The atomic unit of software work that is authorized to create, modify or obsolesce
components within a configuration baseline is called a software change orders ( SCO )
The basic fields of the SCO are Title, description, metrics, resolution, assessment &
disposition
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Change management
II.Configuration Baseline
A configuration baseline is a named collection of software components &Supporting
documentation that is subjected to change management & is upgraded, maintained, tested,
statuses & obsolesced a unit
There are generally two classes of baselines
External Product Release
Internal testing Release
Three levels of baseline releases are required for most Systems
1. Major release (N)
2. Minor Release (M)
3. Interim (temporary) Release (X)
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Major release represents a new generation of the product or project
A minor release represents the same basic product but with enhanced features, performance
or quality.
Major & Minor releases are intended to be external product releases that are persistent &
supported for a period of time.
An interim release corresponds to a developmental configuration that is intended to be
transient.
Once software is placed in a controlled baseline all changes are tracked such that a distinction
must be made for the cause of the change. Change categories are
Type 0: Critical Failures (must be fixed before release)
Type 1: A bug or defect either does not impair (Harm) the usefulness of the system or can be
worked around
Type 2: A change that is an enhancement rather than a response to a defect Type
3: A change that is necessitated by the update to the environment
Type 4: Changes that are not accommodated by the other categories.
Change Management
III Configuration Control Board (CCB)
A CCB is a team of people that functions as the decision
Authority on the content of configuration baselines
A CCB includes:
1. Software managers
2. Software Architecture managers
3. Software Development managers
4. Software Assessment managers
5. Other Stakeholders who are integral to the maintenance of the controlled
software delivery system?
Infrastructure
The organization infrastructure provides the organization9s capital assets
including two key artifacts - Policy & Environment
I Organization Policy:
A Policy captures the standards for project software development processes
The organization policy is usually packaged as a handbook that defines the life cycles & the
process primitives such as
 Major milestones
 Intermediate Artifacts
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 Engineering repositories
 Metrics
 Roles & Responsibilities
Infrastructure
II Organization Environment
The Environment that captures an inventory of tools which are building blocks from which
project environments can be configured efficiently & economically
Stakeholder Environment
Many large scale projects include people in external organizations that represent other
stakeholders participating in the development process they might include
 Procurement agency contract monitors
 End-user engineering support personnel
 Third party maintenance contractors
 Independent verification & validation contractors
 Representatives of regulatory agencies & others.
These stakeholder representatives also need to access to development resources so that they
can contribute value to overall effort. These stakeholders will be access through on-line
An on-line environment accessible by the external stakeholders allow them to participate in
the process a follows
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Accept & use executable increments for the hands-on evaluation.
Use the same on-line tools, data & reports that the development organization uses to manage
& monitor the project
Avoid excessive travel, paper interchange delays, format translations, paper * shipping
costs & other overhead cost
PROJECT CONTROL & PROCESS INSTRUMENTATION
INTERODUCTION: Software metrics are used to implement the activities and products of the software
development process. Hence, the quality of the software products and the achievements in the development
process can be determined using the software metrics.
Need for Software Metrics:
 Software metrics are needed for calculating the cost and schedule of a software product with great
accuracy.
 Software metrics are required for making an accurate estimation of the progress.
 The metrics are also required for understanding the quality of the software product.
INDICATORS:
An indicator is a metric or a group of metrics that provides an understanding of the software process
or software product or a software project. A software engineer assembles measures and produce metrics
from which the indicators can be derived.
Two types of indicators are:
(i) Management indicators.
(ii) Quality indicators.
Management Indicators
The management indicators i.e., technical progress, financial status and staffing progress are used to
determine whether a project is on budget and on schedule. The management indicators that indicate
financial status are based on earned value system.
Quality Indicators
The quality indicators are based on the measurement of the changes occurred in software.
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SEVEN CORE METRICS OF SOFTWARE PROJECT
Software metrics instrument the activities and products of the software development/integration
process. Metrics values provide an important perspective for managing the process. The most useful metrics
are extracted directly from the evolving artifacts.
There are seven core metrics that are used in managing a modern process.
Seven core metrics related to project control:
Management Indicators Quality Indicators
□ Work and Progress □ Change traffic and stability
□ Budgetedcost andexpenditures □ Breakage and modularity
□ Staffing andteamdynamics □ Rework and adaptability
□ Mean time between failures (MTBF) and maturity
MANAGEMENT INDICATORS:
Work and progress
This metric measure the work performed over time. Work is the effort to be accomplished to
complete a certain set of tasks. The various activities of an iterative development project can be measured
by defining a planned estimate of the work in an objective measure, then tracking progress (work completed
overtime) against that plan.
The default perspectives of this metric are:
Software architecture team: - Use cases demonstrated.
Software development team: - SLOC under baseline change management, SCOs closed Software
assessment team: - SCOs opened, test hours executed and evaluation criteria meet. Software
management team: - milestones completed.
The below figure shows expected progress for a typical project with three major releases
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Fig: work and progress
Budgeted cost and expenditures
This metric measures cost incurred over time. Budgeted cost is the planned expenditure profile over
the life cycle of the project. To maintain management control, measuring cost expenditures over the project
life cycle is always necessary. Tracking financial progress takes on an organization - specific format.
Financial performance can be measured by the use of an earned value system, which provides highly
detailed cost and schedule insight. The basic parameters of an earned value system, expressed in units of
dollars, are as follows:
Expenditure Plan - It is the planned spending profile for a project over its planned schedule. Actual
progress - It is the technical accomplishment relative to the planned progress underlying the spending
profile.
Actual cost: It is the actual spending profile for a project over its actual schedule. Earned
value: It is the value that represents the planned cost of the actual progress. Cost variance:
It is the difference between the actual cost and the earned value.
Schedule variance: It is the difference between the planned cost and the earned value. Of all
parameters in an earned value system, actual progress is the most subjective
Assessment: Because most managers know exactly how much cost they have incurred and how much
schedule they have used, the variability in making accurate assessments is centered in the actual progress
assessment. The default perspectives of this metric are cost per month, full-time staff per month and
percentage of budget expended.
Staffing and team dynamics
This metric measure the personnel changes over time, which involves staffing additions and
reductions over time. An iterative development should start with a small team until the risks in the
requirements and architecture have been suitably resolved. Depending on the overlap of iterations and other
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project specific circumstances, staffing can vary. Increase in staff can slow overall project progress as new
people consume the productive team of existing people in coming up to speed. Low attrition of good people
is a sign of success. The default perspectives of this metric are people per month added and people per
month leaving.
These three management indicators are responsible for technical progress, financial status and
staffing progress.
. Fig: work and progress
Fig: staffing and Team dynamics
QUALITY INDICATORS:
Change traffic and stability:
This metric measures the change traffic over time. The number of software change orders opened
and closed over the life cycle is called change traffic. Stability specifies the relationship between opened
versus closed software change orders. This metric can be collected by change type, by release, across all
releases, by term, by components, by subsystems, etc.
The below figure shows stability expectation over a healthy project’s life cycle
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Fig: Change traffic and stability
Breakage and modularity
This metric measures the average breakage per change over time. Breakage is defined as the average
extent of change, which is the amount of software baseline that needs rework and measured in source
lines of code, function points, components, subsystems, files or other units.
Modularity is the average breakage trend over time. This metric can be collected by rewoke SLOC
per change, by change type, by release, by components and by subsystems.
Rework and adaptability:
This metric measures the average rework per change over time. Rework is defined as the average
cost of change which is the effort to analyze, resolve and retest all changes to software baselines.
Adaptability is defined as the rework trend over time. This metric provides insight into rework
measurement. All changes are not created equal. Some changes can be made in a staff- hour, while others
take staff-weeks. This metric can be collected by average hours per change, by change type, by release, by
components and by subsystems.
MTBF and Maturity:
This metric measures defect rater over time. MTBF (Mean Time Between Failures) is the average
usage time between software faults. It is computed by dividing the test hours by the number of type 0 and
type 1 SCOs. Maturity is defined as the MTBF trend over time.
Software errors can be categorized into two types deterministic and nondeterministic. Deterministic
errors are also known as Bohr-bugs and nondeterministic errors are also called as Heisen-bugs. Bohr-bugs
are a class of errors caused when the software is stimulated in a certain way such as coding errors. Heisen-
bugs are software faults that are coincidental with a certain probabilistic occurrence of a given situation,
such as design errors. This metric can be collected by failure counts, test hours until failure, by release, by
components and by subsystems.
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These four quality indicators are based primarily on the measurement of software change across
evolving baselines of engineering data.
LIFE -CYCLE EXPECTATIONS:
METRICS AUTOMATION:
Many opportunities are available to automate the project control activities of a software project. A Software
Project Control Panel (SPCP) is essential for managing against a plan. This panel integrates data from multiple
sources to show the current status of some aspect of the project. The panel can support standard features and
provide extensive capability for detailed situation analysis. SPCP is one example of metrics automation
approach that collects, organizes and reports values and trends extracted directly from the evolving engineering
artifacts.
SPCP:
To implement a complete SPCP, the following are necessary.
 Metrics primitives - trends, comparisons and progressions
 A graphical user interface.
 Metrics collection agents
 Metrics data management server
 Metrics definitions - actual metrics presentations for requirements progress, implementation
progress, assessment progress, design progress and other progress dimensions.
 Actors - monitor and administrator.
Monitor defines panel layouts, graphical objects and linkages to project data. Specific monitors
called roles include software project managers, software development team leads, software architects and
customers. Administrator installs the system, defines new mechanisms, graphical objects and linkages. The
whole display is called a panel. Within a panel are graphical objects, which are types of layouts such as dials
and bar charts for information. Each graphical object displays a metric. Apanel contains a number of
graphical objects positioned in a particular geometric layout. A metric shown in a graphical object is labeled
with the metric type, summary level and insurance name (line of code, subsystem, server1). Metrics can be
displayed in two modes
3 value, referring to a given point in time and graph referring to multiple and consecutive points in time.
Metrics can be displayed with or without control values. A control value is an existing expectation
either absolute or relative that is used for comparison with a dynamically changing metric. Thresholds are
examples of control values.
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The basic fundamental metrics classes are trend, comparison and progress.
The format and content of any project panel are configurable to the software project manager's
preference for tracking metrics of top-level interest. The basic operation of an SPCP can be described by the
following top -level use case.
i. Start the SPCP
ii. Select a panel preference
iii. Select a value or graph metric
iv. Select to superimpose controls
v. Drill down to trend
vi. Drill down to point in time.
vii. Drill down to lower levels of information
viii. Drill down to lower level of indicators.
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UNIT V
CCPDS-R Case Study and Future Software Project Management
Practices
This appendix presents a detailed case study of a successful software project that followed
many of the techniques presented in this book. Successful here means on budget, on
schedule, and satisfactory to the customer. The Command Center Processing and Display
Sys-tem-Replacement (CCPDS-R) project was performed for the U.S. Air Force by TRW
Space and Defense in Redondo Beach, California. The entire project included systems
engineering, hardware procurement, and software development, with each of these three
major activities consuming about one-third of the total cost. The schedule spanned 1987
through 1994.
The software effort included the development of three distinct software systems totaling more
than one million source lines of code. This case study focuses on the initial software
development, called the Common Subsystem, for which about 355,000 source lines were
developed. The Common Subsystem effort also produced a reusable architecture, a mature
process, and an integrated environment for efficient development of the two software
subsystems of roughly similar size that followed. This case study therefore represents about
one-sixth of the overall CCPDS-R project effort.
Although this case study does not coincide exactly with the management process presented in
this book nor with all of today's modern technologies, it used most of the same techniques
and was managed to the same spirit and priorities. TRW delivered
Key Points a An objective case study is a true indicator of a mature organization and a mature
project process. The software industry needs more case studies like CGPDS-R.
a The metrics histories were all derived directly from the artifacts of the project's process.
These data were used to manage the project and were embraced by practitioners, managers,
and stakeholders.
a CCPDS-R was one of the pioneering projects that practiced many modern management
approaches. a This appendix provides a practical context that is relevant to the techniques,
disciplines, and opinions provided throughout this book.
the system on budget and on schedule, and the users got more than they expected. TRW was
awarded the Space and Missile Warning Systems Award for Excellence in 1991 for
"continued, sustained performance in overall systems engineering and project execution." A
project like CCPDS-R could be developed far more efficiently today. By incorporating
current technologies and improved processes, environments, and levels of automation, this
project could probably be built today with equal quality in half the time and at a quarter of the
cost.
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Some of today9s popular software cost models are not well matched to an iterative software
process focused an architecture-first approach Many cost estimators are still using a
conventional process experience base to estimate a modern project profile A next-
generation software cost model should explicitly separate architectural engineering from
application production, just as an architecture-first process does. Two major improvements in
next-generation software cost estimation models: Separation of the engineering stage from
the production stage will force estimators to differentiate between architectural scale and
implementation size. Rigorous design notations such as UML will offer an opportunity to
define units of measure for scale that are more standardized and therefore can be automated
and tracked. Modern Software Economics: Changes that provide a good description of what
an organizational manager should strive for in making the transition to a modern process: 1.
Finding and fixing a software problem after delivery costs 100 times more than fixing the
problem in early design phases 2. You can compress software development schedules 25% of
nominal, but no more. 3. For every $1 you spend on development, you will spend $2 on
maintenance. 4. Software development and maintenance costs are primarily a function of the
number of source lines of code 5. Variations among people account for the biggest
differences in software productivity. 6. The overall ratio of software to hardware costs is still
growing 3 in 1955 it was 15:85; in 1985 85:15 7. Only about 15% of software development
effort is devoted to programming 8. Software systems and products typically cost 3 times as
much per SLOC as individual software programs. 9. Walkthroughs catch 60% of the errors.
10. 80% of the contribution comes from 20% of the contributors.
Next-Generation Software Economics
Next-generation software economics is being practiced by some advanced software
organizations. Many of the techniques, processes, and methods described in this book's
process framework have been practiced for several years. However, a mature, modern
process is nowhere near the state of the practice for the average software organization.
introduces several provocative hypotheses about the future of software economics. A general
structure is proposed for a cost estimation model that would be better suited to the process
framework
new approach would improve the !accuracy and precision of software cost estimates, and
would accommodate dramatic improvements in software economies of scale. Such
improvements will be enabled by advances in software development environments. Boehm's
benchmarks of conventional software project performance and describe, in objective terms,
how the process framework should improve the overall software economics achieved by a
project or organization.
Key Points
▲ Next-generation software economics should reflect better economies of scale and
improved return on investment profiles. These are the real indicators of a mature industry.
▲ Further technology advances in round-trip engineering are critical to making the next
quantum leap in software economics.
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▲ Future cost estimation models need to be based on better primitive units defined from
well-understood software engineering notations such as the Unified Modeling Language.
Modern Process Transitions
Successful software management is hard work. Technical breakthroughs, process
breakthroughs, and new tools will make it easier, but management discipline will continue to
be the crux of software project success. New technological advances will be accompanied by
new opportunities for software applications, new dimensions of complexity, new avenues of
automation, and new customers with different priorities. Accommodating these changes will
perturb many of our ingrained software management values and priorities. However, striking
a balance among requirements, designs, and plans will remain the underlying objective of
future software management endeavors, just as it is today.
numerous projects have been practicing some of these disciplines for years. However, many
of the techniques and disciplines suggested herein will necessitate a significant paradigm
shift. Some of these changes will be resisted by certain stakeholders or by certain factions
within a project or organization. It is not always easy to separate cultural resistance from
objective resistance. summarizes some of the important culture shifts to be prepared for in
order to avoid as many sources of friction as possible in transitioning successfully to a
modern process.
Key Points
▲ The transition to modern software
1 processes and technologies necessitates i several culture shifts that will not ; always be easy
to achieve.
▲ Lessons learned in transitioning organizations to a modern process have exposed several
recurring themes of success that represent important culture
( shifts from conventional practice.
▲ A significant transition should be attempted on a significant project. Pilot i projects do not
generally attract top tal-; ent, and top talent is crucial to the success of any significant
transition.
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