Mutation testing is a technique that involves modifying code to generate "mutants" in order to test test quality. MuTalk is a mutation testing tool for Smalltalk that generates mutants by applying mutation "operators" that make small changes to code, such as changing logical operators. Tests are then run to determine if they can detect and "kill" the mutants. Surviving mutants indicate untested code cases. MuTalk optimizes the process by only mutating and testing covered code. Mutation testing is effective because complex faults are often coupled to simple faults detected by killing mutants.
Having a reliable test suite is incredibly useful when making changes to an existing codebase, both big and small. Mutation testing frameworks run tests against slightly-changed source code in order to detect whether the tests are actually checking the different paths of logic through the application. The aim is to improve the robustness of your test suite, and give you confidence that you aren't introducing any unintended changes.
This presentation gives an overview of mutation testing, along with worked examples in JavaScript of how it catches gaps and improves test coverage.
An introduction to unit testing using Visual Studio, C#, xUnit.net, and Moq. What it is, what is isn't, why we don't do it, how to design for testability, what to test, test driven development, unit testing frameworks, mocking libraries, how to get started.
Having a reliable test suite is incredibly useful when making changes to an existing codebase, both big and small. Mutation testing frameworks run tests against slightly-changed source code in order to detect whether the tests are actually checking the different paths of logic through the application. The aim is to improve the robustness of your test suite, and give you confidence that you aren't introducing any unintended changes.
This presentation gives an overview of mutation testing, along with worked examples in JavaScript of how it catches gaps and improves test coverage.
An introduction to unit testing using Visual Studio, C#, xUnit.net, and Moq. What it is, what is isn't, why we don't do it, how to design for testability, what to test, test driven development, unit testing frameworks, mocking libraries, how to get started.
This presentation is part of one of my webinar in clean code webinar series. The contents are slightly edited to share the information in public domain. In this presentation, I tried to provide detailed introduction to code refactoring practice.
This presentation will be useful for software architects/Managers,developers and QAs. Do share your feedback in comments.
YouTube Link: https://youtu.be/8UfQ8quw0Eg
(**Test Automation Masters Program: https://www.edureka.co/masters-program/automation-testing-engineer-training **)
This Edureka PPT on "What is Integration Testing?" will help you get in-depth knowledge on integration testing and why it is important to subject software builds to integration tests before moving on to next level of testing.
Levels of Software Testing
What is Integration Testing?
Different Approaches to Integration Testing
How to do Integration Testing?
Examples of Integration Testing
Integration Testing Challenges & Best Practices
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How To Write A Test Case In Software Testing | EdurekaEdureka!
YouTube Link: https://youtu.be/KxelISpFqOY
(** Test Automation Masters Program: https://www.edureka.co/masters-progra... **)
This Edureka PPT on "Test Case in Software Testing" will give you in-depth knowledge on how to write a Test Case in Software Testing. The following are the topics covered in the session:
Software Testing Documentation
Test Case in Software Testing
Test Case Format
Test Case Design Technique
Test Case Guidelines
Demo: How to write a test case?
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Software Testing Blog playlist: http://bit.ly/2UXwdJm
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With a pre-requisite of ensuring an application's flawless functioning, this PPT sheds light on what functional testing entails with its importance to enhance an application's quality. Get to know more on Functional Testing Services, Functional Testing Types, Smoke Testing, Sanity Testing, Regression Testing with this presentation and stay tuned for our upcoming ones.
Slides from Software Testing Techniques course offered at Kansas State University in Spring'16 and Spring'17. Entire course material can be found at https://github.com/rvprasad/software-testing-course.
This presentation is part of one of my webinar in clean code webinar series. The contents are slightly edited to share the information in public domain. In this presentation, I tried to provide detailed introduction to code refactoring practice.
This presentation will be useful for software architects/Managers,developers and QAs. Do share your feedback in comments.
YouTube Link: https://youtu.be/8UfQ8quw0Eg
(**Test Automation Masters Program: https://www.edureka.co/masters-program/automation-testing-engineer-training **)
This Edureka PPT on "What is Integration Testing?" will help you get in-depth knowledge on integration testing and why it is important to subject software builds to integration tests before moving on to next level of testing.
Levels of Software Testing
What is Integration Testing?
Different Approaches to Integration Testing
How to do Integration Testing?
Examples of Integration Testing
Integration Testing Challenges & Best Practices
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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How To Write A Test Case In Software Testing | EdurekaEdureka!
YouTube Link: https://youtu.be/KxelISpFqOY
(** Test Automation Masters Program: https://www.edureka.co/masters-progra... **)
This Edureka PPT on "Test Case in Software Testing" will give you in-depth knowledge on how to write a Test Case in Software Testing. The following are the topics covered in the session:
Software Testing Documentation
Test Case in Software Testing
Test Case Format
Test Case Design Technique
Test Case Guidelines
Demo: How to write a test case?
Selenium playlist: https://goo.gl/NmuzXE
Selenium Blog playlist: http://bit.ly/2B7C3QR
Software Testing Blog playlist: http://bit.ly/2UXwdJm
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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With a pre-requisite of ensuring an application's flawless functioning, this PPT sheds light on what functional testing entails with its importance to enhance an application's quality. Get to know more on Functional Testing Services, Functional Testing Types, Smoke Testing, Sanity Testing, Regression Testing with this presentation and stay tuned for our upcoming ones.
Slides from Software Testing Techniques course offered at Kansas State University in Spring'16 and Spring'17. Entire course material can be found at https://github.com/rvprasad/software-testing-course.
Mutation testing is a process to verify the correctness of our tests. It adds a new metric, "mutation coverage", that complements the line coverage to improve our software.
Kill the mutants and test your tests - Roy van RijnNLJUG
Quis custodiet ipsos custodes? Better known as: *Who watches the watchmen?* We are all writing tests, doing TDD, BDD. We measure the quality of the tests with line coverage or (even better) branch coverage. This gives you a false sense of security. I've seen projects with tests which have 100% branch coverage but not a single assertion! This is where mutation testing helps out. By creating broken mutated instances of your codebase (mutants) this should result in failing unit tests. This way we can verify that slight code changes (like real life bugs) actually break your tests. In this talk I'll explain what mutation testing is and how it works. We'll also compare some Java frameworks (PIT, Jester, Jumble) that enable automatic mutation testing in your continuous build and how you can start doing mutation testing *right now*.
Mutation Testing: Leaving the Stone Age. FOSDEM 2017Alex Denisov
For decades developers try to build a bug-free software. Numerous techniques and metrics were developed. However, there is still a need for an approach that can both assert program domain and provide some reliable metrics. And such approach exists. It is called Mutation Testing.
https://fosdem.org/2017/schedule/event/mutation_testing/
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This time it was the microcosm that brought us a few interesting bugs. We have checked the open-source project μManager with our analyzer PVS-Studio. This project is a software package for automated microscope image acquisition.
Must.kill.mutants. TopConf Tallinn 2016Gerald Muecke
Mutation Testing has been around for almost 20 years. Originated in academic research it has found its way into the developer’s toolbox being easy to setup, use and producing valuable results. But what is mutation testing? It’s a practice to determine the actual value of an automated test suite and automatically explore parts of the code that have yet been untested, unveiling surprises even to experienced test automation developers. Given a test suite that runs successfully, mutation testing will inject changes to the production code based on a set of rules and reruns the test to determine if the test will fail. Depending on the size of the code base the execution time increases exponentially due to the sheer amount of permutations, requiring thorough planning, focus and prioritization.
Stop Flying Blind! Quantifying Risk with Monte Carlo SimulationSam McAfee
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SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
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• How a better user experience drives measurable business benefits
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Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
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8. How does it work?
2nd Step: Try to Kill the Mutant
A Killer
The “Mutant” tries to kill the Mutant!
All tests run The Mutant Survives!!!
The Test Suite
A test fails or errors The Mutant Dies
9. Meaning…
The Mutant Survives The case generated by the mutant
is not tested
The Mutant Dies The case generated by the mutant is
tested
10. Example: The mutant survives
DebitCard>>= anotherDebitCard
^(type = anotherDebitCard type) and: [ number = anotherDebitCard number ]
Operator: Change #and: by #or:
DebitCard>>= anotherDebitCard
^(type = anotherDebitCard type) or: [ number = anotherDebitCard number ]
DebitCardTest>>testDebitCardWithSameNumberShouldBeEqual
self assert: (DebitCard visaNumbered: 123) = (DebitCard visaNumbered: 123).
11. Example: The mutant dies
DebitCard>>= anotherDebitCard
^(type = anotherDebitCard type) and: [ number = anotherDebitCard number ]
Operator: Change #and: by #or:
DebitCard>>= anotherDebitCard
^(type = anotherDebitCard type) or: [ number = anotherDebitCard number ]
DebitCardTest>>testDebitCardWithSameNumberShouldBeEqual
self assert: (DebitCard visaNumbered: 123) = (DebitCard visaNumbered: 123).
DebitCardTest >>testDebitCardWithDifferentNumberShouldBeDifferent
self deny: (DebitCard visaNumbered: 123) = (DebitCard visaNumbered: 789).
14. How does it work? - Summary
• Changes the original source code with
special “operators” to generate “Mutants”
• Run the test suite related to the changed
code
• If a test errors or fails Kills the mutant
• If all tests run The Mutant survives
• Surviving Mutants show not tested cases
The Important Thing!
17. MuTalk – How does it work?
• Runs the test to be sure that all run
• For each method m
• For each operator o
• Changes m AST using o
• Compiles mutated code
• Changes method dictionary
• Run the tests
18. MuTalk – Operators
• Boolean messages
• Remove #not
• Replace #and: with #eqv:
• Replace #and: with #nand:
• Replace #and: with #or:
• Replace #and: with #secondArgResult:
• Replace #and: with false
• Replace #or: First Condition with false
• Replace #or: Second Condition with false
• Replace #or: with #and:
• Replace #or: with #xor:
19. MuTalk – Operators
• Magnitude messages
• Replace #'<=' with #<
• Replace #'<=' with #=
• Replace #'<=' with #>
• Replace #'>=' with #=
• Replace #'>=' with #>
• Replace #'~=' with #=
• Replace #< with #>
• Replace #= with #'~='
• Replace #> with #<
• Replace #max: with #min:
• Replace #min: with #max:
20. MuTalk – Operators
• Collection messages
• Remove at:ifAbsent:
• Replace #reject: with #select:
• Replace #select: with #reject:
• Replace Reject block with [:each | false]
• Replace Reject block with [:each | true]
• Replace Select block with [:each | false]
• Replace Select block with [:each | true]
• Replace detect: block with [:each | false] when #detect:ifNone:
• Replace detect: block with [:each | true] when #detect:ifNone:
• Replace do block with [:each |]
• Replace ifNone: block with [] when #detect:ifNone:
• Replace inject:aValue into:aBlock with aValue
• Replace sortBlock:aBlock with sortBlock:[:a :b| true]
21. MuTalk – Operators
• Number messages
• Replace #* with #/
• Replace #+ with #-
• Replace #- with #+
• Replace #/ with #*
22. MuTalk – Operators
• Flow control messages
• Remove Exception Handler Operator
• Replace #ifFalse: receiver with false
• Replace #ifFalse: receiver with true
• Replace #ifFalse: with #ifTrue:
• Replace #ifFalse:IfTrue: receiver with false
• Replace #ifFalse:IfTrue: receiver with true
• Replace #ifTrue: receiver with false
• Replace #ifTrue: receiver with true
• Replace #ifTrue: with #ifFalse:
• Replace #ifTrue:ifFalse: receiver with false
• Replace #ifTrue:ifFalse: receiver with true
24. Is not new … - History
Begins in 1971, R. Lipton, “Fault Diagnosis of
Computer Programs”
Generally accepted in 1978, R. Lipton et al,
“Hints on test data selection: Help for the
practicing programmer”
25. Why is not widely used?
Maturity Problem: Because Testing is not
widely used YET!
(Although it is increasing)
26. Why is not widely used?
Integration Problem: Inability to successfully
integrate it into the software development
process
(TDD plays a key role now)
27. Why is not widely used?
Technical Problem: It is a Brute Force
technique!
29. Aconcagua
• Number of Tests: 666
• Number of Mutants: 1005
• Time to create a mutant/compile/link/run:
10 secs. each aprox.?
• Total time:
– 6693300 seconds
– 1859 hours, 15 minutes
30. Another way of doing it…
CreditCard>>= anotherCreditCard
^(anotherCreditCard isKindOf: self class) and: [ number =
anotherCreditCard number ]
CreditCard>>= anotherCreditCard
MutantId = 12 ifTrue: [ ^(anotherCreditCard isKindOf: self class) or: [
number = anotherCreditCard number ].
MutantId = 13 ifTrue: [ ^(anotherCreditCard isKindOf: self class)
nand: [ number = anotherCreditCard number ].
MutantId = 14 ifTrue: [ ^(anotherCreditCard isKindOf: self class) eqv: [
number = anotherCreditCard number ].
31. Aconcagua
• Number of Tests: 666
• Number of Mutants: 1005
• Time to create the
metamutant/compile/link: 2 minutes?
• Time to run the tests per mutant: 1 sec
• Total time:
– 1125 seconds
– 18 minutes 45 seconds
32. MuTalk Optimizations
Running Strategies
Mutate all methods, run all tests per Mutate covered methods, run all
mutant tests per mutant
– Create a mutant for each method – Takes coverage running all tests
– Run all the test for each mutant – Mutate only covered methods
– Disadvantage: Slower strategy – Run all methods per mutant
– Relies on coverage
Mutate all methods, run only test Mutate covered methods, run only test
that cover mutated method that covered mutated methods
– Run coverage keeping for each – Run coverage keeping for each
method the tests that covered it method the tests that covered it
– Create a mutant for each method – Create a mutant for only covered
– For each mutant, run only the methods
tests that covered the original – For each mutant, run only the tests
method that covered the original method
36. MuTalk - Terminated Mutants
• Take the time it runs each test the first
time
• If the test takes more thant 3 times,
terminate it
37. Let’s redefine MuTalk as…
Mutation Testing Tool for Smalltalk (Pharo
and Squeak) that uses meta-facilities to
run faster and provide inmediate feedback
38. Work in progress
• Operators Categorization based on how
useful they are to detect errors
• Filter Operators on View
• Cancel process
39. Future work
• Make Operators more “inteligent”
• a = b ifTrue: [ … ]
• a = b ifFalse: [] is equivalent to a ~= b ifTrue: []
• Suggest tests using not killed mutants
• Use MuTalk to test MuTalk?
40. Why does it work?
“Complex faults are coupled to simple faults
in such a way that a test data set that detects
all simple faults in a program will detect most
complex faults” (Coupling effect)
Demonstrated in 1995, K. Wah, “Fault coupling in finite
bijective functions”
41. Why does it work?
“In practice, if the software contains a fault,
there will usually be a set of mutants that can
only be killed by a test case that also detects
that fault”
Geist et al, “Estimation and enhancement of real-time
software reliability through mutation analysis”, 1992
43. How does it compare to
coverage?
• Does not replaces coverage because
some methods do not generate mutants
• But:
• Mutants on not covered methods will survive
• It provides better insight than coverage
• Method Coverage fails with long
methods/conditions/loops/etc.