AI-powered test intelligence plugin for predictive test selection, flaky detection, and coverage optimization
npm install @claude-flow/plugin-test-intelligence


A comprehensive test intelligence plugin combining reinforcement learning for optimal test selection with graph neural networks for code-to-test mapping. The plugin enables predictive test selection (run only tests likely to fail), flaky test detection, mutation testing optimization, and test coverage gap identification while integrating seamlessly with popular testing frameworks.
- Predictive Test Selection: Select tests most likely to fail based on code changes using RL
- Flaky Test Detection: Identify and analyze flaky tests with root cause classification
- Coverage Gap Analysis: Identify test coverage gaps using code-test graph analysis
- Mutation Testing Optimization: Optimize mutation testing for efficiency within time budgets
- Test Generation Suggestions: Suggest test cases for uncovered code paths
``bash`
npm install @claude-flow/plugin-test-intelligence
`bash`
npx claude-flow plugins install --name @claude-flow/plugin-test-intelligence
`typescript
import { TestIntelligencePlugin } from '@claude-flow/plugin-test-intelligence';
// Initialize the plugin
const testIntel = new TestIntelligencePlugin({
historyPath: './data/test-history',
framework: 'vitest',
projectPath: './'
});
// Predictive test selection
const selectedTests = await testIntel.selectPredictive({
changes: {
files: ['src/auth/login.ts', 'src/utils/validation.ts'],
gitRef: 'HEAD'
},
strategy: 'balanced',
budget: { maxTests: 50, confidence: 0.95 }
});
// Detect flaky tests
const flakyTests = await testIntel.flakyDetect({
scope: { historyDepth: 100 },
analysis: ['intermittent_failures', 'timing_sensitive'],
threshold: 0.1
});
// Identify coverage gaps
const gaps = await testIntel.coverageGaps({
targetPaths: ['src/'],
coverageType: 'semantic',
prioritization: 'risk'
});
`
Select tests most likely to fail based on code changes.
`typescript
const result = await mcp.invoke('test/select-predictive', {
changes: {
files: ['src/services/UserService.ts', 'src/models/User.ts'],
gitDiff: '...diff content...',
gitRef: 'feature-branch'
},
strategy: 'fast_feedback',
budget: {
maxTests: 30,
maxDuration: 300, // 5 minutes
confidence: 0.95
}
});
// Returns:
// {
// selectedTests: [
// { name: 'UserService.createUser', file: 'tests/UserService.test.ts', priority: 1, failureProbability: 0.82 },
// { name: 'User.validate', file: 'tests/User.test.ts', priority: 2, failureProbability: 0.75 },
// ...
// ],
// estimatedDuration: 45,
// coverageEstimate: 0.89,
// skippedTests: 120,
// timeSaved: '4m 30s'
// }
`
Identify and analyze flaky tests.
`typescript
const result = await mcp.invoke('test/flaky-detect', {
scope: {
testSuite: 'integration',
historyDepth: 200
},
analysis: [
'intermittent_failures',
'timing_sensitive',
'order_dependent',
'resource_contention'
],
threshold: 0.1
});
// Returns:
// {
// flakyTests: [
// {
// name: 'API.rateLimit.test',
// flakinessScore: 0.23,
// failureRate: 0.15,
// rootCause: 'timing_sensitive',
// details: 'Relies on 100ms timeout that occasionally exceeds',
// recommendation: 'Use fake timers or increase timeout margin',
// lastFailed: '2024-01-14T10:30:00Z'
// },
// {
// name: 'Database.concurrent.test',
// flakinessScore: 0.18,
// failureRate: 0.08,
// rootCause: 'resource_contention',
// details: 'Competes for database connections with other tests',
// recommendation: 'Isolate test database or use connection pooling'
// }
// ],
// summary: {
// totalFlakyTests: 8,
// quarantineSuggested: 3,
// estimatedCITimeSaved: '12 minutes per run'
// }
// }
`
Identify test coverage gaps.
`typescript
const result = await mcp.invoke('test/coverage-gaps', {
targetPaths: ['src/services/', 'src/controllers/'],
coverageType: 'semantic',
prioritization: 'risk',
minCoverage: 80
});
// Returns:
// {
// gaps: [
// {
// file: 'src/services/PaymentService.ts',
// function: 'processRefund',
// currentCoverage: 45,
// riskScore: 0.85,
// complexity: 'high',
// recommendation: 'Add tests for error handling paths',
// suggestedTestCases: [
// 'should handle partial refund',
// 'should reject refund exceeding original amount',
// 'should handle payment provider timeout'
// ]
// },
// ...
// ],
// summary: {
// averageCoverage: 72,
// highRiskUncovered: 5,
// estimatedTestsNeeded: 15
// }
// }
`
Optimize mutation testing for efficiency.
`typescript
const result = await mcp.invoke('test/mutation-optimize', {
targetPath: 'src/utils/validation.ts',
budget: 100, // Max mutations to run
strategy: 'ml_guided',
mutationTypes: ['arithmetic', 'logical', 'boundary', 'null_check']
});
// Returns:
// {
// selectedMutations: [
// {
// location: { line: 45, column: 12 },
// type: 'boundary',
// original: 'age >= 18',
// mutated: 'age > 18',
// killedBy: ['validateAge.boundary.test'],
// priority: 1
// },
// ...
// ],
// mutationScore: 0.82,
// survivingMutants: 18,
// testGaps: [
// { mutation: 'null_check at line 67', reason: 'No test covers null input' }
// ],
// timeSpent: '45s',
// timeVsFullRun: '12x faster'
// }
`
Suggest test cases for uncovered code.
`typescript
const result = await mcp.invoke('test/generate-suggest', {
targetFunction: 'src/auth/validateToken.ts:validateJWT',
testStyle: 'unit',
framework: 'vitest',
edgeCases: true,
mockStrategy: 'minimal'
});
// Returns:
// {
// suggestedTests: [
// {
// name: 'should validate a valid JWT token',
// type: 'happy_path',
// code:
// test('should validate a valid JWT token', () => {
// const token = createTestToken({ userId: '123', exp: Date.now() + 3600000 });
// const result = validateJWT(token);
// expect(result.valid).toBe(true);
// expect(result.payload.userId).toBe('123');
// });
// },
// {
// name: 'should reject expired token',
// type: 'edge_case',
// code:
// test('should reject expired token', () => {
// const token = createTestToken({ userId: '123', exp: Date.now() - 1000 });
// const result = validateJWT(token);
// expect(result.valid).toBe(false);
// expect(result.error).toBe('TOKEN_EXPIRED');
// });`
// },
// ...
// ],
// requiredMocks: ['jsonwebtoken.verify'],
// setupCode: '...'
// }
`typescript
interface TestIntelligenceConfig {
// Data paths
historyPath: string; // Path to test history storage
projectPath: string; // Project root path
// Framework
framework: 'jest' | 'vitest' | 'pytest' | 'junit' | 'mocha';
testPattern: string; // Glob pattern for test files
// Performance
maxMemoryMB: number; // WASM memory limit (default: 512)
maxCpuTimeSeconds: number; // Operation timeout (default: 60)
// Learning
learningEnabled: boolean; // Enable continuous learning (default: true)
minHistoryDepth: number; // Minimum runs before predictions (default: 50)
}
`
| Framework | Language | Support Level |
|-----------|----------|---------------|
| Jest | JavaScript/TypeScript | Full |
| Vitest | JavaScript/TypeScript | Full |
| pytest | Python | Full |
| JUnit | Java | Partial |
| Mocha | JavaScript | Partial |
| RSpec | Ruby | Basic |
This plugin analyzes tests but does NOT execute them directly:
- Returns test selection lists only
- User runs tests via their own CI/CD pipeline
- No arbitrary code execution in WASM
| Constraint | Value | Rationale |
|------------|-------|-----------|
| Memory Limit | 512MB max | Sufficient for test analysis |
| CPU Time Limit | 60 seconds | Prevent runaway analysis |
| No Test Execution | Analysis only | Prevent arbitrary code execution |
| No Network Access | Enforced | Prevent data exfiltration |
| Sandboxed History | Per-project | Prevent cross-project leakage |
All inputs are validated using Zod schemas:
`typescript`
// All inputs validated:
- Git diffs: Maximum 1MB
- File lists: Maximum 1000 files
- History depth: 10-10000 runs
- Max duration: 1-86400 seconds (24 hours)
- Confidence level: 0.5-1.0
- Test names: Alphanumeric with standard punctuation, max 500 characters
- Framework: Enum validated against supported frameworks
`typescript`
const rateLimits = {
'test/select-predictive': { requestsPerMinute: 60, maxConcurrent: 5 },
'test/flaky-detect': { requestsPerMinute: 10, maxConcurrent: 2 },
'test/coverage-gaps': { requestsPerMinute: 30, maxConcurrent: 3 },
'test/mutation-optimize': { requestsPerMinute: 5, maxConcurrent: 1 },
'test/generate-suggest': { requestsPerMinute: 30, maxConcurrent: 3 }
};
| Metric | Target |
|--------|--------|
| Test selection | <1s for 10K tests |
| Flaky detection | <5s for 1000 test runs |
| Coverage gap analysis | <10s for 100K LOC |
| Mutation optimization | 80% mutation score in 20% time |
| CI time reduction | 60-80% |
The plugin continuously learns from test execution history:
``
Execution History --> SONA Learning --> RL Policy
| | |
v v v
[fail rates] [pattern bank] [selection model]
[timings] [failure modes] [prioritization]
[coverage] [correlations] [budget allocation]
- micro-hnsw-wasm: Fast code-to-test similarity matchingruvector-learning-wasm
- : RL-based test selection and prioritizationruvector-gnn-wasm
- : Code-test dependency graphs for impact analysisruvector-sparse-inference-wasm
- : Efficient flaky test pattern detectionsona
- : Continuous learning from test execution historyistanbul-lib-coverage`: Coverage report parsing
-
| Plugin | Description | Use Case |
|--------|-------------|----------|
| @claude-flow/plugin-code-intelligence | Code analysis | Impact analysis for test prioritization |
| @claude-flow/plugin-perf-optimizer | Performance optimization | Test performance profiling |
| @claude-flow/plugin-financial-risk | Risk analysis | Test risk scoring for critical paths |
MIT License
Copyright (c) 2026 Claude Flow
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