Mutation Testing
Table of Contents
Overview
Mutation testing assesses test suite quality by introducing small changes (mutations) to source code and verifying that tests fail. If tests don't catch a mutation, it indicates gaps in test coverage or test quality. This technique helps identify weak or ineffective tests.
When to Use
- Evaluating test suite effectiveness
- Finding untested code paths
- Improving test quality metrics
- Validating critical business logic is well-tested
- Identifying redundant or weak tests
- Measuring real test coverage beyond line coverage
- Ensuring tests actually verify behavior
Quick Start
Minimal working example:
# Install Stryker
npm install --save-dev @stryker-mutator/core @stryker-mutator/jest-runner
# Initialize configuration
npx stryker init
# Run mutation testing
npx stryker run
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents | |---|---| | Stryker for JavaScript/TypeScript | Stryker for JavaScript/TypeScript | | PITest for Java | PITest for Java | | mutmut for Python | mutmut for Python | | Mutation Testing Reports | Mutation Testing Reports |
Best Practices
✅ DO
- Target critical business logic for mutation testing
- Aim for 80%+ mutation score on important code
- Review survived mutants to improve tests
- Mark equivalent mutants to exclude them
- Use mutation testing in CI for critical modules
- Test boundary conditions thoroughly
- Verify actual behavior, not just code execution
❌ DON'T
- Expect 100% mutation score everywhere
- Run mutation testing on all code (too slow)
- Ignore equivalent mutants
- Test getters/setters with mutations
- Run mutations on generated code
- Skip mutation testing on complex logic
- Focus only on line coverage