After being occupied with some commitments for about two months, I finally got time to write the next article 😊. This post is on Mutation Testing, a white box testing, to test program code. Mutation testing is also useful for test automation code, databases, software models and other artifacts in software engineering. View the below tutorial or read on...
What is Mutation Testing in software testing? Basically, in Mutation Testing, you make a change (a mutation) to your program and run your tests with test data. Mutation Testing finds if your existing tests and test data are useful or not. Using Mutation Testing, you could know which sections of your program are tested poorly. Also, you could identify your tests that never find any mutants (changed copies of your program). In the example below, the program on the left is the original program and the program on the right is it's mutant.
Mutation Testing process (Mutation Analysis)
1) You test your original program with all your tests and test data. If any test fails, you need to fix your program or that test or it's test data.
2) Once your program passes all the tests, you create mutants by using any mutation operator (e.g delete a statement, duplicate a statement, exchange operators etc.) and test your mutants. Each test run on any mutant should ideally fail, because a mutant is a changed copy of your program.
3) If a test run on any mutant passes, you should find out the reason (e.g. the mutated code is not run or the mutant is functionally "equivalent" to your program). In order to find more mutants, you need to update your existing tests (or test data) and/ or write new tests (with test data). Also, if you update your test set or test data, you need to repeat the above process from step 1).
Want to learn Mutation Testing more? Like Mutation Analysis in detail, Mutation Score and Mutation Testing assumptions? Then, please view the complete Mutation Testing tutorial. Thank you.
