What is mutation testing?

Mutation testing is a technique where small, deliberate changes (mutants) are injected into your code. If your tests still pass despite these changes, it indicates the tests are not robust enough to catch logic errors.

Which tools does this skill use?

This skill utilizes Stryker for TypeScript and JavaScript environments (supporting Vitest and npm/bun) and mutmut for Python projects.

Should I aim for a 100% mutation score?

While 100% is the ideal, it is often impractical due to 'equivalent mutants'—changes that don't actually alter the program's observable behavior. A score of 80-90% is typically considered excellent.

What is a 'survived' mutant?

A 'survived' mutant is a code change that was introduced but did not cause any tests to fail. This usually means your tests are missing an assertion or a specific boundary case.

How does mutation testing differ from code coverage?

Code coverage only measures which lines of code were executed during a test. Mutation testing measures the effectiveness of your assertions by verifying if they actually detect changes in logic.

Mutation Testing

Name: Mutation Testing
Author: secondsky

bysecondsky

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セキュリティとテスト

Validates test suite effectiveness by introducing deliberate code mutations to identify and fix weak test cases.

概要

This skill empowers Claude to go beyond simple code coverage by performing mutation testing using Stryker for TypeScript/JavaScript and mutmut for Python. It works by injecting small, intentional faults into your source code—if your tests still pass, they are marked as 'survived,' indicating a gap in your test logic. This is an essential tool for developers building high-reliability systems who need to ensure their test suites actually catch bugs rather than just executing lines of code.

主な機能

Guidance on fixing common test smells and boundary condition gaps
Automated mutation analysis for TypeScript/JS (Stryker) and Python (mutmut)
21 GitHub stars
Support for incremental testing to focus only on changed files
Detailed HTML report generation and interpretation
Identification of 'survived' mutants to pinpoint weak assertions

ユースケース

Setting quality gates in CI/CD pipelines based on mutation scores
Improving reliability for mission-critical business logic and edge cases
Auditing existing test suites to find tests that pass even when logic is broken

概要

主な機能

Guidance on fixing common test smells and boundary condition gaps
Automated mutation analysis for TypeScript/JS (Stryker) and Python (mutmut)
21 GitHub stars
Support for incremental testing to focus only on changed files
Detailed HTML report generation and interpretation
Identification of 'survived' mutants to pinpoint weak assertions

ユースケース

Setting quality gates in CI/CD pipelines based on mutation scores
Improving reliability for mission-critical business logic and edge cases
Auditing existing test suites to find tests that pass even when logic is broken