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Software Reliability
Presented by:
Gurkamal Rakhra
Mahadev Kiran
Syed Hannan Yunus
Contents
• Software Reliability(SR) definition
• Key concepts
• Factors influencing SR
• SR Methodologies
• SR Models
• SR Applications
• Summary
What is reliability?
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.
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)
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
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
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
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
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
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
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.
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
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
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.
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.,)
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.
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.
Classification of Models
Reference: Software Testing and Quality Assurance-
Naik,Tripathy
Classification of Models (contd..)
Reference: Software Testing and Quality Assurance-
Naik,Tripathy
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
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.
Example models
• TBF - J-M De-Eutrophication.
• FC - Goel-Okumoto NHPP Model.
• FS - Mills seeding Model.
• IDB - Ramamoorthy and Bastani Model.
SR Modeling Flow Chart
Reference: Software Testing and Quality Assurance-
Naik,Tripathy
Applications of SR Models
 The applicability of these models can be assessed during
 Design Phase.
 Unit Testing.
 Integration Testing.
 Operational Phases.
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.
Questions?

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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.