Qe Mutation Testing

Mutation Testing

<default_to_action> When validating test quality or improving test effectiveness: 1. MUTATE code (change + to -, >= to >, remove statements) 2. RUN tests against each mutant 3. VERIFY tests catch mutations (kill mutants) 4. IDENTIFY surviving mutants (tests need improvement) 5. STRENGTHEN tests to kill surviving mutants

Quick Mutation Metrics:

• Mutation Score = Killed / (Killed + Survived)
• Target: > 80% mutation score
• Surviving mutants = weak tests

Critical Success Factors:

• High coverage ≠ good tests (100% coverage, 0% assertions)
• Mutation testing proves tests actually catch bugs
• Focus on critical code paths first

</default_to_action>

Quick Reference Card

When to Use

• Evaluating test suite quality
• Finding gaps in test assertions
• Proving tests catch bugs
• Before critical releases

Mutation Score Interpretation

Common Mutation Operators

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How Mutation Testing Works

// Original code
function isAdult(age) {
  return age >= 18; // ← Mutant: change >= to >
}

// Strong test (catches mutation)
test('18 is adult', () => {
  expect(isAdult(18)).toBe(true); // Kills mutant!
});

// Weak test (mutation survives)
test('19 is adult', () => {
  expect(isAdult(19)).toBe(true); // Doesn't catch >= vs >
});
// Surviving mutant → Test needs boundary value

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Using Stryker

# Install
npm install --save-dev @stryker-mutator/core @stryker-mutator/jest-runner

# Initialize
npx stryker init

Configuration:

{
  "packageManager": "npm",
  "reporters": ["html", "clear-text", "progress"],
  "testRunner": "jest",
  "coverageAnalysis": "perTest",
  "mutate": [
    "src/**/*.ts",
    "!src/**/*.spec.ts"
  ],
  "thresholds": {
    "high": 90,
    "low": 70,
    "break": 60
  }
}

Run:

npx stryker run

Output:

Mutation Score: 87.3%
Killed: 124
Survived: 18
No Coverage: 3
Timeout: 1

---

Fixing Surviving Mutants

// Surviving mutant: >= changed to >
function calculateDiscount(quantity) {
  if (quantity >= 10) { // Mutant survives!
    return 0.1;
  }
  return 0;
}

// Original weak test
test('large order gets discount', () => {
  expect(calculateDiscount(15)).toBe(0.1); // Doesn't test boundary
});

// Fixed: Add boundary test
test('exactly 10 gets discount', () => {
  expect(calculateDiscount(10)).toBe(0.1); // Kills mutant!
});

test('9 does not get discount', () => {
  expect(calculateDiscount(9)).toBe(0); // Tests below boundary
});

---

Agent-Driven Mutation Testing

// Analyze mutation score and generate fixes
await Task("Mutation Analysis", {
  targetFile: 'src/payment.ts',
  generateMissingTests: true,
  minScore: 80
}, "qe-test-generator");

// Returns:
// {
//   mutationScore: 0.65,
//   survivedMutations: [
//     { line: 45, operator: '>=', mutant: '>', killedBy: null }
//   ],
//   generatedTests: [
//     'test for boundary at line 45'
//   ]
// }

// Coverage + mutation correlation
await Task("Coverage Quality Analysis", {
  coverageData: coverageReport,
  mutationData: mutationReport,
  identifyWeakCoverage: true
}, "qe-coverage-analyzer");

---

Agent Coordination Hints

Memory Namespace

aqe/mutation-testing/
├── mutation-results/*   - Stryker reports
├── surviving/*          - Surviving mutants
├── generated-tests/*    - Tests to kill mutants
└── trends/*             - Mutation score over time

Fleet Coordination

const mutationFleet = await FleetManager.coordinate({
  strategy: 'mutation-testing',
  agents: [
    'qe-test-generator',     // Generate tests for survivors
    'qe-coverage-analyzer',  // Coverage correlation
    'qe-quality-analyzer'    // Quality assessment
  ],
  topology: 'sequential'
});

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Related Skills

• tdd-london-chicago - Write effective tests first
• test-design-techniques - Boundary value analysis
• quality-metrics - Measure test effectiveness

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Remember

High code coverage ≠ good tests. 100% coverage but weak assertions = useless. Mutation testing proves tests actually catch bugs.

Focus on critical paths first. Don't mutation test everything - prioritize payment, authentication, data integrity code.

With Agents: Agents run mutation analysis, identify surviving mutants, and generate missing test cases to kill them. Automated improvement of test quality.