What is a mutation score?

A mutation score is a metric that represents the percentage of intentionally introduced code faults (mutants) that your test suite successfully detected and 'killed'.

How does mutation testing differ from code coverage?

While code coverage measures which lines of code were executed during a test, mutation testing measures whether the tests actually verify the logic on those lines by checking if they fail when the logic is changed.

What are 'surviving mutants'?

Surviving mutants are code changes introduced by the runner that the test suite failed to detect, indicating a gap where code is executed but its output or behavior isn't being properly validated.

When should I use the Mutation Test Runner skill?

Use this skill when you want to ensure your tests are high-quality, specifically before major releases or when working on complex logic where standard coverage isn't enough to guarantee reliability.

Mutation Test Runner

Name: Mutation Test Runner
Author: intent-solutions-io

byintent-solutions-io

보안 및 테스팅

Validates test suite quality by introducing code mutations and measuring the detection effectiveness of existing test cases.

소개

The Mutation Test Runner skill empowers Claude to perform advanced mutation testing, a technique that evaluates the actual effectiveness of a test suite by injecting small, intentional logic errors into the source code. Unlike traditional code coverage which only measures which lines were executed, this skill calculates a mutation score by determining if your tests are capable of 'killing' these mutants. It helps developers identify 'surviving mutants'—specific logic paths that are covered by tests but not actually validated—ensuring mission-critical code is robustly protected against regressions.

주요 기능

Identification of specific test gaps and 'surviving' code mutants
0 GitHub stars
Detailed mutation score calculation and survival rate reporting
Context-aware suggestions for improving test logic based on results
Automated test execution against mutated code versions
Automatic generation of code mutations such as operator and logic swaps

사용 사례

Validating the reliability of test suites for critical modules like authentication or payments
Improving overall code quality by strengthening tests based on mutation analysis
Identifying logic gaps that traditional line coverage tools fail to detect

소개

주요 기능

Identification of specific test gaps and 'surviving' code mutants
0 GitHub stars
Detailed mutation score calculation and survival rate reporting
Context-aware suggestions for improving test logic based on results
Automated test execution against mutated code versions
Automatic generation of code mutations such as operator and logic swaps

사용 사례

Validating the reliability of test suites for critical modules like authentication or payments
Improving overall code quality by strengthening tests based on mutation analysis
Identifying logic gaps that traditional line coverage tools fail to detect