Mutation Testing

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• 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:

# 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