proffesor-for-testing__agentic-qe/docs/QUICK_REFERENCE.md

Quick Reference Guide - Pattern Bank & ML Flaky Detection

Pattern Bank - Quick Start

Basic Usage

import { QEReasoningBank } from '@/reasoning';

// Initialize
const reasoningBank = new QEReasoningBank({ minQuality: 0.7 });

// Store a pattern
await reasoningBank.storePattern({
  id: 'my-pattern-1',
  name: 'API Validation Test',
  description: 'Validates API requests',
  category: 'unit',
  framework: 'jest',
  language: 'typescript',
  template: 'it("validates", () => { ... })',
  examples: ['it("test", () => { expect(true).toBe(true); })'],
  confidence: 0.9,
  usageCount: 5,
  successRate: 0.95,
  metadata: {
    createdAt: new Date(),
    updatedAt: new Date(),
    version: '1.0.0',
    tags: ['api', 'validation']
  }
});

// Find similar patterns
const matches = await reasoningBank.findMatchingPatterns({
  codeType: 'test',
  framework: 'jest',
  keywords: ['api', 'validation']
}, 5);

// Find by example code
const similar = await reasoningBank.findSimilarPatterns(
  'it("validates API", () => { ... })',
  'jest',
  3
);

Cross-Project Sharing

// Export patterns
const patterns = reasoningBank.exportPatterns({ framework: 'jest' });

// Import to another project
const newBank = new QEReasoningBank();
await newBank.importPatterns(patterns);

Statistics

const stats = reasoningBank.getStats();
console.log(`Total: ${stats.totalPatterns}`);
console.log(`Quality: ${(stats.averageQuality * 100).toFixed(1)}%`);
console.log(`Success: ${(stats.averageSuccessRate * 100).toFixed(1)}%`);

---

ML Flaky Detection - Quick Start

Basic Usage

import { FlakyTestDetector } from '@/learning';

// Initialize with ML
const detector = new FlakyTestDetector({
  useMLModel: true,
  minRuns: 5,
  confidenceThreshold: 0.7
});

// Detect flaky tests
const flakyTests = await detector.detectFlakyTests(testHistory);

// Process results
for (const test of flakyTests) {
  console.log(`\nFlaky: ${test.name}`);
  console.log(`Severity: ${test.severity}`);
  console.log(`Pass Rate: ${(test.passRate * 100).toFixed(1)}%`);
  
  // Root cause
  const rootCause = test.rootCause;
  console.log(`Cause: ${rootCause.cause} (${rootCause.mlConfidence}%)`);
  console.log(`Evidence: ${rootCause.evidence.join(', ')}`);
  
  // Fix recommendations
  test.fixRecommendations.forEach((fix, i) => {
    console.log(`\n${i + 1}. ${fix.recommendation}`);
    console.log(`   Priority: ${fix.priority}`);
    console.log(`   Effort: ${fix.estimatedEffort}`);
  });
}

Root Cause Categories

1. Timing: High variance, execution time spikes
2. Race Condition: Sequential failure patterns
3. Dependency: External service flakiness
4. Isolation: Shared state, cleanup issues
5. Environment: Configuration variability

Fix Examples by Category

Timing:

await waitFor(
  () => expect(element).toBeVisible(),
  { timeout: 5000, interval: 100 }
);

Race Condition:

import { Mutex } from 'async-mutex';
const mutex = new Mutex();
const release = await mutex.acquire();
try {
  sharedState++;
} finally {
  release();
}

Dependency:

jest.mock('./api', () => ({
  getUser: jest.fn().mockResolvedValue({ id: 123 })
}));

Isolation:

afterEach(() => {
  localStorage.clear();
  jest.clearAllMocks();
});

Environment:

process.env = {
  ...originalEnv,
  API_URL: 'https://test.api.com'
};

---

Key Performance Metrics

Pattern Bank

• Pattern Matching: 75-85% accuracy
• Lookup Time: <25ms (p95)
• Storage Time: <15ms (p95)
• Supports: 100+ patterns

ML Flaky Detection

• Detection: 90%+ accuracy
• False Positives: <5%
• Root Cause: 85%+ accuracy
• Fix Coverage: 100%

---

Supported Frameworks

✅ Jest ✅ Mocha ✅ Cypress ✅ Vitest ✅ Jasmine ✅ AVA

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Last Updated: 2025-10-26