Software Reliability
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Software reliability is defined as the probability of failure-free operation of software over a specified time period and environment. Key factors influencing reliability include fault count, which is impacted by code size/complexity and development processes, and operational profile, which describes how users operate the system. Software reliability methodologies aim to improve dependability through fault avoidance, tolerance, removal, and forecasting, with the latter using models to predict reliability mathematically based on factors like time between failures or failure counts.
Software Reliability
- 1. Software Reliability Presented by: Gurkamal Rakhra Mahadev Kiran Syed Hannan Yunus
- 2. Contents • Software Reliability(SR) definition • Key concepts • Factors influencing SR • SR Methodologies • SR Models • SR Applications • Summary
- 4. Reliability • Reliability is a broad concept. • Reliability is one of the metrics that are used to measure quality. • It is a user-oriented quality factor relating to system operation. • Intuitively, if the users of a system rarely experience failure, the system is considered to be more reliable than one that fails more often. • A system without faults is considered to be highly reliable.
- 5. Key concepts • Failure If observable outcome of a program execution is different from the expected outcome. • Fault Cause of failure. • Time If the time gap between two successive failures is short, we say that the system is less reliable. Two types of time models are: • Execution time() • Calendar time (t)
- 6. Key concepts cont. • MTTF: Mean Time To Failure • MTTR: Mean Time To Repair • MTBF: Mean Time Between Failures (= MTTF + MTTR) Figure: Relationship between MTTR, MTTF, and MTBF. Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 7. Definition of Software Reliability • First definition oSoftware reliability is defined as the probability of failure-free operation of a software system for a specified time in a specified environment. Key elements of the above definition oProbability of failure-free operation oLength of time of failure-free operation oA given execution environment Example oThe probability that a PC in a store is up and running for eight hours without crash is 0.99. Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 8. Definition cont. • Second definition • Failure intensity is a measure of the reliability of a software system operating in a given environment. • Example: An air traffic control system fails once in two years. • Comparing the two • The first puts emphasis on MTTF, whereas the second on count. Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 9. Factors influencing software reliability User’s perception- Reliability of a software depends upon two categories of information 1)The number of faults present in the software 2)The ways user operate the system-Operational profile Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 10. Fault count is influenced by following: • Size and complexity of code • Characteristics of development process used • Education, experience and training of development personnel • Operational Environment Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 11. Operational Profile • An OP describes how actual users operate a system. • Two ways to represent operational profiles • Tabular • Graphical Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 12. Use of OP in different ways • Use an OP as a guiding document in designing user interfaces. • Use an OP to design early version of a software for release • Use an OP to determine where to put more resources in a software. Note: For accurate estimation of reliability of a system, test the system in the same way it will be actually used in the field.
- 13. Software reliability methodologies Critical systems (spacecraft, aircraft, nuclear power plant etc. ) require a high level of dependability in their operation. Dependability means: 1)Fault avoidance 2)Fault tolerance 3)Fault removal 4)Fault forecasting Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 14. Fault avoidance • Prevent the introduction of faults during the development of the software. How? • Use standards and guidelines -How to implement the code? -When and where to use functions, pointers etc., • Use formal methods -state m/c to verify system working • Methods against software aging -to prevent memory leaks-system crash
- 15. Fault tolerance • Used to address the shortcoming of fault avoidance How? By mitigating the risks cos -there will be some potential or hidden faults remaining in software.
- 16. Fault removal • Aim at detecting and fixing faults once the code has been developed. How? • Testing techniques • Using various methods and verification • Analysis ( Dynamic , Semantic etc.,)
- 17. Fault forecasting • Estimating the presence of faults. • Occurrence and consequences of failure. • Main aim of fault forecasting is predicting the reliability of a software product reliability. • They are mainly concerned with reliability models.
- 18. Why Software Reliability Models? • The fault forecasting methodologies includes the reliability models. • Return us the reliability of the software or predict the reliability of the software.
- 19. Classification of Models Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 20. Classification of Models (contd..) Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 21. Time Dependent Models Time between failures models (TBF): In this class of models under study is the time between failures. Failure Count Models (FC): The interest of this class of models is in the number of faults and failures in specified time intervals
- 22. Time Independent Models Fault Seeding Models (FS): Program has unknown number of indigenous faults , to this a known number of faults are seeded. Input Domain Based Models (IDB): An estimate of the reliability of the program is obtained from the failures observed during execution of the sample test cases.
- 23. Example models • TBF - J-M De-Eutrophication. • FC - Goel-Okumoto NHPP Model. • FS - Mills seeding Model. • IDB - Ramamoorthy and Bastani Model.
- 24. SR Modeling Flow Chart Reference: Software Testing and Quality Assurance- Naik,Tripathy
- 25. Applications of SR Models The applicability of these models can be assessed during Design Phase. Unit Testing. Integration Testing. Operational Phases.
- 26. Summary • Software reliability is defined as the probability of failure-free operation of a software system for a specified time in a specified environment. • Factors influencing SR are fault count and operational profile • Dependability means fault avoidance, fault tolerance, fault removal and fault forecasting. • SR models helps in predicting the reliability of the software using mathematical approach.
- 27. Questions?