Evaluate test suite quality by introducing code mutations and verifying tests catch them. Use for mutation testing, test quality, mutant detection, Stryker, PITest, and test effectiveness analysis.

Mutation Testing Table of Contents [Overview]( overview) [When to Use]( when to use) [Quick Start]( quick start) [Reference Guides]( reference guides) [Best Practices]( best practices) 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: Reference Guides Detailed implementations in the references/ directory: Guide Contents [Stryker for JavaScript/TypeScript](references/stryker for javascripttypescript.md) Stryker for JavaScript/TypeScript [PITest for Java](references/pitest for java.md) PITest for Java [mutmut for Python](references/mutmut for python.md) mutmut for Python [Mutation Testing Reports](references/mutation testing reports.md) 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

mutation-testing