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Software Reliability
Presented by:Vishal Padme
D.G. RUPAREL College Of Arts Commerce And Science
|| Roll No:3059 || TYBsc CS 2020-21 ||
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.
eg.
Failure :You Failed In Exam
Fault: You didn't study/No one Helped You/Undefined
Continue...
• 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(𝜏):
Amount of time given by System To
Software Operation
• Calendar time (t ):
Overall Time Spend During Operation
By User.
Reliability metrics
I] MTTF: Mean Time To Failure
Working Software Failure Occurs
Reliability metrics
II] MTTR: Mean Time To Repair
Reliability metrics
III] MTBF: Mean Time Between Failures
MTTF
MTTR
MTBF MTBF
MTTR MTTR
MTTF MTTF
Time
Reliability metrics
IV] POFOD : Probability of Failure on Demand
• POFOD is the likelihood that the system will fail when a
service request is made. A POFOD of 0.001 means that
one out of a thousand service requests may result in
failure.
• POFOD is an important measure for safety critical systems
and should be kept as low as possible. It is relevant for
many safety-critical systems with the exception of
management components, such as an emergency
shutdown system in a chemical plant.
Reliability metrics
V] ROCOF : Rate Of Occurrences Of
Failure
• ROCOF is the frequency of occurrence with which unexpected
behavior is likely to occur.
• A ROCOF of 2 / 100 means that two failures are likely to occur in each
100 operational time units. This metric is sometimes called the failure
intensity.
• It is relevant for operating systems and transaction-processing
systems where the system has to process a large number of similar
requests that are relatively frequent; for example, credit-card
processing systems, airline booking systems, etc.
Reliability metrics
VI] AVAIL : Availability
• Availability is the probability that the system is
available for use at a given time.
• An availability of 0.998 means that in every 1000 time units, the
system is likely to be available for 998 of these.
Software Reliability
• First definition:
Software 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:
• Probability of failure-free operation
• Length of time of failure-free operation
• A given execution environment
 Example :
The probability that a PC in a store is up and running for
eight hours without crash is 0.99.
SR-Defn
• Second definition
• Failure intensity is a measure of Defining the reliability of a
software system operating in a given environment.
• Example : An air traffic control system fails once in two years.
Comparing Definitions
First Definition Second Definition
Based On MTTF.
Time From Failure Free Software
to->First Failure.
It Describes How Much Time
Software can be Free Of Any
Failure.
Based On Frequency Of Failures [
ROCOF ].
Count Of Failure States Time
interval 't'.
It Describes How
Vulnerable/Stable Software is in
Time interval.
Factors
• 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
SR-Influencing Factors
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
SR-Influencing Factors
Software Operational Env. is influenced by following:
• Change in Environment
• Change in Infrastructure OR technology.
• Huge Change in Requirements.
• Lack of Maintenance / Difficult to maintain.
Methodologies
• Critical systems (spacecraft, aircraft, nuclear power plant etc. )
require a high level of dependability in their operation.
• Dependability Methodologies:
• 1)Fault avoidance
• 2)Fault tolerance
• 3)Fault removal
• 4)Fault forecasting
SR-Methodologies
1] 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 management to verify system working
• Methods against software aging
-to prevent memory leaks-system crash
SR-Methodologies
2]Fault Tolerance:
• Fault tolerance refers to the ability of a system (computer, network, cloud cluster, etc.)
to continue operating without interruption when one or more of its components fail.
• The objective of creating a fault-tolerant system is to prevent disruptions arising from
a single point of failure, ensuring the high relilability.
• Software systems that are backed up by other software instances. For example, a
database with customer information can be continuously replicated to another
machine. If the primary database goes down, operations can be automatically
redirected to the second database.
SR-Methodologies
3]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.,)
SR-Methodologies
4]Fault Forecasting:
• Estimating the presence of faults.
• Occurrence and consequences of failure.
• Main aim of fault forecasting is predicting the reliability of a software
• They are mainly concerned with reliability models.
SUMMARY
Factors influencing SR are fault
count and operational profile
Factors
fault avoidance, fault tolerance,
fault removal and fault forecasting.
Dependability
MTTF: Mean Time ToFailure
MTTR: Mean Time ToRepair
MTBF: Mean Time Between Failures
POFOD: Probability Of Failure On
Demand
ROCOF: Rate Of Occurrences Of Failures
AVAIL: Availability Of Service
Performance Metrics
Software reliability is defined as the probability of failure-free operation of a software system
for a specified time in a specified environment.
Thanks .

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Software Reliability_CS-3059_VISHAL_PADME.pptx

  • 1. Software Reliability Presented by:Vishal Padme D.G. RUPAREL College Of Arts Commerce And Science || Roll No:3059 || TYBsc CS 2020-21 ||
  • 2.
  • 3. 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.
  • 4.
  • 5. Key Concepts • Failure If observable outcome of a program execution is different from the expected outcome. • Fault Cause of failure. eg. Failure :You Failed In Exam Fault: You didn't study/No one Helped You/Undefined
  • 6. Continue... • 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(𝜏): Amount of time given by System To Software Operation • Calendar time (t ): Overall Time Spend During Operation By User.
  • 7.
  • 8. Reliability metrics I] MTTF: Mean Time To Failure Working Software Failure Occurs
  • 9. Reliability metrics II] MTTR: Mean Time To Repair
  • 10. Reliability metrics III] MTBF: Mean Time Between Failures MTTF MTTR MTBF MTBF MTTR MTTR MTTF MTTF Time
  • 11. Reliability metrics IV] POFOD : Probability of Failure on Demand • POFOD is the likelihood that the system will fail when a service request is made. A POFOD of 0.001 means that one out of a thousand service requests may result in failure. • POFOD is an important measure for safety critical systems and should be kept as low as possible. It is relevant for many safety-critical systems with the exception of management components, such as an emergency shutdown system in a chemical plant.
  • 12. Reliability metrics V] ROCOF : Rate Of Occurrences Of Failure • ROCOF is the frequency of occurrence with which unexpected behavior is likely to occur. • A ROCOF of 2 / 100 means that two failures are likely to occur in each 100 operational time units. This metric is sometimes called the failure intensity. • It is relevant for operating systems and transaction-processing systems where the system has to process a large number of similar requests that are relatively frequent; for example, credit-card processing systems, airline booking systems, etc.
  • 13. Reliability metrics VI] AVAIL : Availability • Availability is the probability that the system is available for use at a given time. • An availability of 0.998 means that in every 1000 time units, the system is likely to be available for 998 of these.
  • 14.
  • 15. Software Reliability • First definition: Software 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: • Probability of failure-free operation • Length of time of failure-free operation • A given execution environment  Example : The probability that a PC in a store is up and running for eight hours without crash is 0.99.
  • 16. SR-Defn • Second definition • Failure intensity is a measure of Defining the reliability of a software system operating in a given environment. • Example : An air traffic control system fails once in two years.
  • 17. Comparing Definitions First Definition Second Definition Based On MTTF. Time From Failure Free Software to->First Failure. It Describes How Much Time Software can be Free Of Any Failure. Based On Frequency Of Failures [ ROCOF ]. Count Of Failure States Time interval 't'. It Describes How Vulnerable/Stable Software is in Time interval.
  • 18.
  • 19. Factors • 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
  • 20. SR-Influencing Factors 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
  • 21. SR-Influencing Factors Software Operational Env. is influenced by following: • Change in Environment • Change in Infrastructure OR technology. • Huge Change in Requirements. • Lack of Maintenance / Difficult to maintain.
  • 22.
  • 23. Methodologies • Critical systems (spacecraft, aircraft, nuclear power plant etc. ) require a high level of dependability in their operation. • Dependability Methodologies: • 1)Fault avoidance • 2)Fault tolerance • 3)Fault removal • 4)Fault forecasting
  • 24. SR-Methodologies 1] 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 management to verify system working • Methods against software aging -to prevent memory leaks-system crash
  • 25. SR-Methodologies 2]Fault Tolerance: • Fault tolerance refers to the ability of a system (computer, network, cloud cluster, etc.) to continue operating without interruption when one or more of its components fail. • The objective of creating a fault-tolerant system is to prevent disruptions arising from a single point of failure, ensuring the high relilability. • Software systems that are backed up by other software instances. For example, a database with customer information can be continuously replicated to another machine. If the primary database goes down, operations can be automatically redirected to the second database.
  • 26. SR-Methodologies 3]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.,)
  • 27. SR-Methodologies 4]Fault Forecasting: • Estimating the presence of faults. • Occurrence and consequences of failure. • Main aim of fault forecasting is predicting the reliability of a software • They are mainly concerned with reliability models.
  • 28. SUMMARY Factors influencing SR are fault count and operational profile Factors fault avoidance, fault tolerance, fault removal and fault forecasting. Dependability MTTF: Mean Time ToFailure MTTR: Mean Time ToRepair MTBF: Mean Time Between Failures POFOD: Probability Of Failure On Demand ROCOF: Rate Of Occurrences Of Failures AVAIL: Availability Of Service Performance Metrics Software reliability is defined as the probability of failure-free operation of a software system for a specified time in a specified environment.