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• Metrics for Process and Products: Software measurement,
metrics for software quality.
• Software Measurement: A measurement is a manifestation of the size,
quantity, amount, or dimension of a particular attribute of a product or
process. Software measurement is a titrate impute of a characteristic of a
software product or the software process.
Software Measurement Principles
• The software measurement process can be characterized by five activities-
• Formulation: The derivation of software measures and metrics appropriate for
the representation of the software that is being considered.
• Collection: The mechanism used to accumulate data required to derive the
formulated metrics.
• Analysis: The computation of metrics and the application of mathematical
tools.
• Interpretation: The evaluation of metrics results in insight into the quality of
the representation.
• Feedback: Recommendation derived from the interpretation of product
metrics transmitted to the software team.
Need for Software Measurement
• Software is measured to: Create the quality of the current product or process.
• Anticipate future qualities of the product or process.
• Enhance the quality of a product or process.
• Regulate the state of the project concerning budget and schedule.
• Enable data-driven decision-making in project planning and control.
• Identify bottlenecks and areas for improvement to drive process
improvement activities.
• Ensure that industry standards and regulations are followed.
• Give software products and processes a quantitative basis for evaluation.
• Enable the ongoing improvement of software development practices.
Classification of Software Measurement
• There are 2 types of software measurement:
• Direct Measurement: In direct measurement, the product, process, or
thing is measured directly using a standard scale.
Example:Direct Measure: Cost, effort, length of code (LOC), speed, and
memory are internal attributes that these metrics can measure
• Indirect Measurement: In indirect measurement, the quantity or quality
to be measured is measured using related parameters i.e. by use of
reference.
Example: Indirect Measure: It is used to measure quality, functionality,
complexity, efficiency, reliability, and maintainability along with assessing
external attributes.
• Software Metrics
• A metric is a measurement of the level at which any impute belongs
to a system product or process.
• Software metrics are a quantifiable or countable assessment of the
attributes of a software product.
• There are 4 functions related to software metrics:
• Planning
• Organizing
• Controlling
• Improving
Characteristics of software Metrics
• Quantitative: Metrics must possess a quantitative nature( numerical values).
• Understandable: Metric computation should be easily understood, and the
method of computing metrics should be clearly defined.
• Applicability: Metrics should be applicable in the initial phases of the
development of the software.
• Repeatable: When measured repeatedly, the metric values should be the same
and consistent.
• Economical: The computation of metrics should be economical.
• Language Independent: Metrics should not depend on any programming
language.
• Types of Software Metrics
• Product Metrics: Evaluate the state of the product, tracing risks and undercover
prospective problem areas.
• Examples include lines of code, cyclomatic complexity(stability and level of confidence
in a program), code coverage, defect density, and code maintainability index.
• Process Metrics: PThese metrics are used to optimize the development process and
maintenance activities of software. Examples include effort variance, schedule variance,
defect injection rate, and lead time.
• Effort Variance = ((Actual Effort - Planned Effort) / Planned Effort) * 100. It measures
the difference between the actual effort required to complete a task or project and the
effort that was planned.
• Project Metrics: The project metrics describes the characteristic and
execution of a project.
• Examples include effort estimation accuracy, schedule deviation, cost
variance, and productivity.
• Usually measures-
– Number of software developer
– Staffing patterns over the life cycle of software
– Cost and schedule
– Productivity
Software Quality Metrics
 Software quality metrics are a subset of software metrics that focus on the
quality aspects of the product, process, and project.
 These are more closely associated with process and product metrics than
with project metrics.
Software quality metrics can be further divided into three categories
 Product quality metrics
 In-process quality metrics
 Maintenance quality metrics
Product Quality Metrics This metrics include the following −
 Mean Time to Failure
 Defect Density
 Customer Problems
 Customer Satisfaction
Mean Time to Failure
 It is the time between failures.
 This metric is mostly used with safety critical systems such as the airline
traffic control systems.
Defect Density
 It measures the defects relative to the software size expressed as lines of
code or function point, etc. i.e., it measures code quality per unit.
 This metric is used in many commercial software systems.
Customer Problems :
 It measures the problems that customers encounter when using the
product.
 It contains the customer’s perspective towards the problem space of the
software, which includes the non-defect oriented problems together with
the defect problems.
Customer Satisfaction
 Customer satisfaction is often measured by customer survey data through
the five-point scale −
 Very satisfied
 Satisfied
 Neutral
 Dissatisfied
 Very dissatisfied
In-process quality metrics
 In-process quality metrics deals with the tracking of defect arrival during
formal machine testing for some organizations.
 This metric includes −
 Defect density during machine testing
 Defect arrival pattern during machine testing
 Phase-based defect removal pattern
 Defect removal effectiveness
Maintenance quality metrics
 Although much cannot be done to alter the quality of the product
during this phase, following are the fixes that can be carried out to
eliminate the defects as soon as possible with excellent fix quality.
 Fix backlog and backlog management index
 Fix response time and fix responsiveness
 Fix quality
• Advantages of Software Metrics
• Reduction in cost or budget.
• It helps to identify the particular area for improvising.
• It helps to increase the product quality.
• Managing the workloads and teams.
• Reduction in overall time to produce the product,.
• It helps to determine the complexity of the code and to test the code
with resources.
• It helps in providing effective planning, controlling and managing of
the entire product.
Disadvantages of Software Metrics
• It is expensive and difficult to implement the metrics in some cases.
• Performance of the entire team or an individual from the team can't be
determined. Only the performance of the product is determined.
• Sometimes the quality of the product is not met with the expectation.
• It leads to measure the unwanted data which is wastage of time.
• Measuring the incorrect data leads to make wrong decision making.

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UNIT4(2) OB UNIT II NOTESOB UNIT II NOTES

  • 1. • Metrics for Process and Products: Software measurement, metrics for software quality.
  • 2. • Software Measurement: A measurement is a manifestation of the size, quantity, amount, or dimension of a particular attribute of a product or process. Software measurement is a titrate impute of a characteristic of a software product or the software process.
  • 3. Software Measurement Principles • The software measurement process can be characterized by five activities- • Formulation: The derivation of software measures and metrics appropriate for the representation of the software that is being considered. • Collection: The mechanism used to accumulate data required to derive the formulated metrics. • Analysis: The computation of metrics and the application of mathematical tools. • Interpretation: The evaluation of metrics results in insight into the quality of the representation. • Feedback: Recommendation derived from the interpretation of product metrics transmitted to the software team.
  • 4. Need for Software Measurement • Software is measured to: Create the quality of the current product or process. • Anticipate future qualities of the product or process. • Enhance the quality of a product or process. • Regulate the state of the project concerning budget and schedule. • Enable data-driven decision-making in project planning and control. • Identify bottlenecks and areas for improvement to drive process improvement activities. • Ensure that industry standards and regulations are followed. • Give software products and processes a quantitative basis for evaluation. • Enable the ongoing improvement of software development practices.
  • 5. Classification of Software Measurement • There are 2 types of software measurement: • Direct Measurement: In direct measurement, the product, process, or thing is measured directly using a standard scale. Example:Direct Measure: Cost, effort, length of code (LOC), speed, and memory are internal attributes that these metrics can measure
  • 6. • Indirect Measurement: In indirect measurement, the quantity or quality to be measured is measured using related parameters i.e. by use of reference. Example: Indirect Measure: It is used to measure quality, functionality, complexity, efficiency, reliability, and maintainability along with assessing external attributes.
  • 7. • Software Metrics • A metric is a measurement of the level at which any impute belongs to a system product or process. • Software metrics are a quantifiable or countable assessment of the attributes of a software product. • There are 4 functions related to software metrics: • Planning • Organizing • Controlling • Improving
  • 8. Characteristics of software Metrics • Quantitative: Metrics must possess a quantitative nature( numerical values). • Understandable: Metric computation should be easily understood, and the method of computing metrics should be clearly defined. • Applicability: Metrics should be applicable in the initial phases of the development of the software. • Repeatable: When measured repeatedly, the metric values should be the same and consistent. • Economical: The computation of metrics should be economical. • Language Independent: Metrics should not depend on any programming language.
  • 9. • Types of Software Metrics • Product Metrics: Evaluate the state of the product, tracing risks and undercover prospective problem areas. • Examples include lines of code, cyclomatic complexity(stability and level of confidence in a program), code coverage, defect density, and code maintainability index. • Process Metrics: PThese metrics are used to optimize the development process and maintenance activities of software. Examples include effort variance, schedule variance, defect injection rate, and lead time. • Effort Variance = ((Actual Effort - Planned Effort) / Planned Effort) * 100. It measures the difference between the actual effort required to complete a task or project and the effort that was planned.
  • 10. • Project Metrics: The project metrics describes the characteristic and execution of a project. • Examples include effort estimation accuracy, schedule deviation, cost variance, and productivity. • Usually measures- – Number of software developer – Staffing patterns over the life cycle of software – Cost and schedule – Productivity
  • 11. Software Quality Metrics  Software quality metrics are a subset of software metrics that focus on the quality aspects of the product, process, and project.  These are more closely associated with process and product metrics than with project metrics. Software quality metrics can be further divided into three categories  Product quality metrics  In-process quality metrics  Maintenance quality metrics
  • 12. Product Quality Metrics This metrics include the following −  Mean Time to Failure  Defect Density  Customer Problems  Customer Satisfaction
  • 13. Mean Time to Failure  It is the time between failures.  This metric is mostly used with safety critical systems such as the airline traffic control systems. Defect Density  It measures the defects relative to the software size expressed as lines of code or function point, etc. i.e., it measures code quality per unit.  This metric is used in many commercial software systems.
  • 14. Customer Problems :  It measures the problems that customers encounter when using the product.  It contains the customer’s perspective towards the problem space of the software, which includes the non-defect oriented problems together with the defect problems.
  • 15. Customer Satisfaction  Customer satisfaction is often measured by customer survey data through the five-point scale −  Very satisfied  Satisfied  Neutral  Dissatisfied  Very dissatisfied
  • 16. In-process quality metrics  In-process quality metrics deals with the tracking of defect arrival during formal machine testing for some organizations.  This metric includes −  Defect density during machine testing  Defect arrival pattern during machine testing  Phase-based defect removal pattern  Defect removal effectiveness
  • 17. Maintenance quality metrics  Although much cannot be done to alter the quality of the product during this phase, following are the fixes that can be carried out to eliminate the defects as soon as possible with excellent fix quality.  Fix backlog and backlog management index  Fix response time and fix responsiveness  Fix quality
  • 18. • Advantages of Software Metrics • Reduction in cost or budget. • It helps to identify the particular area for improvising. • It helps to increase the product quality. • Managing the workloads and teams. • Reduction in overall time to produce the product,. • It helps to determine the complexity of the code and to test the code with resources. • It helps in providing effective planning, controlling and managing of the entire product.
  • 19. Disadvantages of Software Metrics • It is expensive and difficult to implement the metrics in some cases. • Performance of the entire team or an individual from the team can't be determined. Only the performance of the product is determined. • Sometimes the quality of the product is not met with the expectation. • It leads to measure the unwanted data which is wastage of time. • Measuring the incorrect data leads to make wrong decision making.