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https://github.com/proffesor-for-testing/agentic-qe.git
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b91627f282
Phase 1: Test Determinism - Create SeededRandom utility with Mulberry32 PRNG (src/utils/SeededRandom.ts) - Migrate 258+ Math.random() calls to SeededRandom across 65+ test files - Add timer test utilities (tests/helpers/timerTestUtils.ts) - Add jest.useFakeTimers() pattern to 13 test files Phase 2: Type Safety (63.5% reduction) - Reduce `any` types from ~1,800 to 656 - Add 50+ new interfaces across agents, core, mcp, cli modules - Fix all TypeScript errors (0 errors, build passes) - Replace Record<string, any> with Record<string, unknown> - Add proper type guards for hook methods (PostTaskData, TaskErrorData) Key improvements: - agents/: 105 → 0 any types (100% reduction) - mcp/: 226 → 102 any types (55% reduction) - cli/: 277 → 168 any types (39% reduction) - core/: 199 → 175 any types (12% reduction) Closes #149 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
326 lines
11 KiB
TypeScript
326 lines
11 KiB
TypeScript
/**
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* Pattern Matching Accuracy Validation Tests
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*
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* Validates the 85%+ matching accuracy claim for QEReasoningBank.
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* Uses a ground truth dataset with known pattern similarities.
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*
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* @module tests/reasoning/accuracy
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*/
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import { describe, it, expect, beforeEach } from '@jest/globals';
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import { QEReasoningBank, TestPattern } from '../../src/reasoning/QEReasoningBank';
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import { createSeededRandom } from '../../src/utils/SeededRandom';
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interface GroundTruthPair {
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pattern1: TestPattern;
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pattern2: TestPattern;
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expectedSimilarity: number; // 0-1 scale
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shouldMatch: boolean;
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}
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describe('Pattern Matching Accuracy', () => {
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let reasoningBank: QEReasoningBank;
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let groundTruthDataset: GroundTruthPair[];
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beforeEach(async () => {
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reasoningBank = new QEReasoningBank();
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groundTruthDataset = createGroundTruthDataset();
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// Store all patterns
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for (const pair of groundTruthDataset) {
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await reasoningBank.storePattern(pair.pattern1);
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await reasoningBank.storePattern(pair.pattern2);
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}
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});
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describe('Matching Accuracy Validation', () => {
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it('should achieve 85%+ matching accuracy on ground truth dataset', async () => {
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let correctMatches = 0;
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let totalComparisons = 0;
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for (const pair of groundTruthDataset) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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const predicted = similarity >= 0.5; // Match threshold
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if (predicted === pair.shouldMatch) {
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correctMatches++;
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}
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totalComparisons++;
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}
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const accuracy = correctMatches / totalComparisons;
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expect(accuracy).toBeGreaterThanOrEqual(0.85);
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expect(totalComparisons).toBeGreaterThanOrEqual(100);
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console.log(`Matching Accuracy: ${(accuracy * 100).toFixed(2)}%`);
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console.log(`Correct: ${correctMatches}/${totalComparisons}`);
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});
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it('should have high precision (few false positives)', async () => {
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let truePositives = 0;
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let falsePositives = 0;
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for (const pair of groundTruthDataset) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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const predicted = similarity >= 0.5;
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if (predicted && pair.shouldMatch) {
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truePositives++;
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} else if (predicted && !pair.shouldMatch) {
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falsePositives++;
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}
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}
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const precision = truePositives / (truePositives + falsePositives);
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expect(precision).toBeGreaterThanOrEqual(0.80);
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console.log(`Precision: ${(precision * 100).toFixed(2)}%`);
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});
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it('should have high recall (few false negatives)', async () => {
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let truePositives = 0;
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let falseNegatives = 0;
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for (const pair of groundTruthDataset) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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const predicted = similarity >= 0.5;
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if (predicted && pair.shouldMatch) {
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truePositives++;
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} else if (!predicted && pair.shouldMatch) {
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falseNegatives++;
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}
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}
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const recall = truePositives / (truePositives + falseNegatives);
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expect(recall).toBeGreaterThanOrEqual(0.80);
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console.log(`Recall: ${(recall * 100).toFixed(2)}%`);
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});
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it('should correctly match very similar patterns', async () => {
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const verySimilarPairs = groundTruthDataset.filter(p => p.expectedSimilarity >= 0.8);
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for (const pair of verySimilarPairs) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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expect(similarity).toBeGreaterThanOrEqual(0.7);
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}
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});
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it('should correctly identify very different patterns', async () => {
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const veryDifferentPairs = groundTruthDataset.filter(p => p.expectedSimilarity <= 0.2);
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for (const pair of veryDifferentPairs) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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expect(similarity).toBeLessThanOrEqual(0.4);
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}
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});
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it('should handle partial matches correctly', async () => {
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const partialPairs = groundTruthDataset.filter(
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p => p.expectedSimilarity > 0.3 && p.expectedSimilarity < 0.7
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);
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for (const pair of partialPairs) {
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const similarity = reasoningBank.calculateSimilarity(pair.pattern1, pair.pattern2);
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// Should be in the partial match range
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expect(similarity).toBeGreaterThan(0.2);
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expect(similarity).toBeLessThanOrEqual(0.8); // Use <= to handle boundary
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}
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});
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});
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describe('Edge Cases', () => {
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it('should handle patterns with identical framework and language', async () => {
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const pattern1: TestPattern = createTestPattern('p1', 'jest', 'typescript', ['api', 'unit']);
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const pattern2: TestPattern = createTestPattern('p2', 'jest', 'typescript', ['api', 'unit']);
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const similarity = reasoningBank.calculateSimilarity(pattern1, pattern2);
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expect(similarity).toBeGreaterThanOrEqual(0.9);
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});
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it('should handle patterns with no common tags', async () => {
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const pattern1: TestPattern = createTestPattern('p1', 'jest', 'typescript', ['api']);
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const pattern2: TestPattern = createTestPattern('p2', 'jest', 'typescript', ['database']);
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const similarity = reasoningBank.calculateSimilarity(pattern1, pattern2);
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// Should still match on framework and language
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expect(similarity).toBeGreaterThan(0);
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expect(similarity).toBeLessThan(0.7);
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});
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it('should handle patterns with different frameworks', async () => {
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const pattern1: TestPattern = createTestPattern('p1', 'jest', 'typescript', ['api']);
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const pattern2: TestPattern = createTestPattern('p2', 'mocha', 'typescript', ['api']);
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const similarity = reasoningBank.calculateSimilarity(pattern1, pattern2);
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// Lower similarity due to framework difference
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expect(similarity).toBeLessThan(0.8);
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});
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});
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describe('Real-World Scenarios', () => {
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it('should match API controller patterns across projects', async () => {
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const project1Pattern: TestPattern = {
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id: 'p1-api',
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name: 'API Controller Test',
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description: 'Test Express.js controller',
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category: 'unit',
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framework: 'jest',
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language: 'typescript',
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template: 'test template',
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examples: ['describe("UserController", () => {})'],
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confidence: 0.9,
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usageCount: 10,
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successRate: 0.85,
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metadata: {
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createdAt: new Date(),
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updatedAt: new Date(),
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version: '1.0.0',
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tags: ['api', 'controller', 'express', 'rest']
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}
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};
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const project2Pattern: TestPattern = {
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id: 'p2-api',
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name: 'REST API Controller Test',
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description: 'Test REST controller endpoints',
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category: 'unit',
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framework: 'jest',
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language: 'typescript',
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template: 'test template',
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examples: ['describe("ProductController", () => {})'],
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confidence: 0.88,
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usageCount: 8,
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successRate: 0.90,
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metadata: {
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createdAt: new Date(),
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updatedAt: new Date(),
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version: '1.0.0',
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tags: ['api', 'controller', 'rest', 'endpoint']
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}
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};
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const similarity = reasoningBank.calculateSimilarity(project1Pattern, project2Pattern);
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// Should be highly similar (same domain, framework, language, overlapping tags)
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expect(similarity).toBeGreaterThanOrEqual(0.75);
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});
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it('should distinguish between unit and integration patterns', async () => {
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const unitPattern: TestPattern = createTestPattern('unit', 'jest', 'typescript', ['unit', 'mock']);
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unitPattern.category = 'unit';
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const integrationPattern: TestPattern = createTestPattern('int', 'jest', 'typescript', ['integration', 'database']);
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integrationPattern.category = 'integration';
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const similarity = reasoningBank.calculateSimilarity(unitPattern, integrationPattern);
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// Different categories should reduce similarity
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expect(similarity).toBeLessThan(0.6);
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});
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});
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});
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/**
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* Create ground truth dataset with 100+ pattern pairs
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*/
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function createGroundTruthDataset(): GroundTruthPair[] {
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const dataset: GroundTruthPair[] = [];
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// Very similar patterns (20 pairs)
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for (let i = 0; i < 20; i++) {
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dataset.push({
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pattern1: createTestPattern(`similar-${i}-a`, 'jest', 'typescript', ['api', 'unit']),
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pattern2: createTestPattern(`similar-${i}-b`, 'jest', 'typescript', ['api', 'unit']),
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expectedSimilarity: 0.95,
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shouldMatch: true
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});
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}
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// Moderately similar patterns (30 pairs)
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for (let i = 0; i < 30; i++) {
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dataset.push({
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pattern1: createTestPattern(`moderate-${i}-a`, 'jest', 'typescript', ['api', 'unit']),
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pattern2: createTestPattern(`moderate-${i}-b`, 'jest', 'typescript', ['api', 'integration']),
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expectedSimilarity: 0.5,
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shouldMatch: true
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});
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}
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// Different patterns (30 pairs)
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for (let i = 0; i < 30; i++) {
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dataset.push({
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pattern1: createTestPattern(`diff-${i}-a`, 'jest', 'typescript', ['api']),
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pattern2: createTestPattern(`diff-${i}-b`, 'mocha', 'javascript', ['e2e']),
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expectedSimilarity: 0.1,
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shouldMatch: false
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});
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}
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// Same framework, different language (10 pairs)
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for (let i = 0; i < 10; i++) {
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dataset.push({
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pattern1: createTestPattern(`lang-${i}-a`, 'jest', 'typescript', ['unit']),
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pattern2: createTestPattern(`lang-${i}-b`, 'jest', 'javascript', ['unit']),
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expectedSimilarity: 0.6,
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shouldMatch: true
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});
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}
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// Same language, different framework (10 pairs)
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for (let i = 0; i < 10; i++) {
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dataset.push({
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pattern1: createTestPattern(`fw-${i}-a`, 'jest', 'typescript', ['unit']),
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pattern2: createTestPattern(`fw-${i}-b`, 'vitest', 'typescript', ['unit']),
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expectedSimilarity: 0.55,
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shouldMatch: true
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});
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}
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return dataset;
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}
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// Seeded random instance for deterministic pattern creation
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const accuracyRng = createSeededRandom(15200);
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/**
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* Helper to create test patterns
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*/
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function createTestPattern(
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id: string,
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framework: 'jest' | 'mocha' | 'vitest' | 'playwright' | 'cypress' | 'jasmine' | 'ava',
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language: 'typescript' | 'javascript' | 'python',
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tags: string[]
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): TestPattern {
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return {
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id,
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name: `Pattern ${id}`,
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description: `Test pattern ${id}`,
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category: 'unit',
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framework,
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language,
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template: `template-${id}`,
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examples: [`example-${id}`],
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confidence: 0.8 + accuracyRng.random() * 0.2,
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usageCount: Math.floor(accuracyRng.random() * 100),
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successRate: 0.7 + accuracyRng.random() * 0.3,
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metadata: {
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createdAt: new Date(),
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updatedAt: new Date(),
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version: '1.0.0',
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tags
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}
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};
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}
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