mirror of
https://github.com/proffesor-for-testing/agentic-qe.git
synced 2026-09-19 08:45:47 +08:00
c3b342a03a
## Summary Successfully fixed all initialization issues and completed Phase 2 integration: - Fixed agent template discovery and copying (18 agents now copy correctly) - Added comprehensive logging throughout init process - Fixed undefined config property serialization bug - All databases initialize correctly (memory.db, patterns.db) - Phase 2 features (learning, patterns, improvement) fully functional ## Bug Fixes 1. **Agent Copy Bug**: Changed from directory copy to individual file copy - Fixed: "Copied 0 agent definitions" → Now copies all 18 agents - Issue: fs.copy with filter wasn't working, changed to per-file copy 2. **Missing Agent**: Created qe-quality-analyzer.md - Was the only missing agent out of 17 required QE agents - Added complete agent definition with AQE hooks integration 3. **Incomplete Fallback**: Updated fallback from 6 to all 17 agents - Ensures all agents are created even if templates not found - Maintains feature parity in all scenarios 4. **Serialization Bug**: Added sanitizeConfig() helper - Fixed: "Cannot read properties of undefined (reading 'replace')" - Issue: jsonfile couldn't serialize config with undefined properties - Solution: Recursive sanitization removes undefined values before write 5. **Config Path Bug**: Fixed target vs source file list confusion - Was passing source files to createMissingAgents instead of target - Now correctly identifies which agents are missing in target ## Improvements - Added detailed path discovery logging with ✓/✗ checkmarks - Show agent template counts and copy progress - Log each config file write with file paths - Added stack traces to all error handlers (removed verbose-only check) - Created sanitizeConfig for robust JSON serialization ## Testing Verified in test project `/tmp/aqe-test-final`: ✅ All 17 QE agents created ✅ memory.db created (221KB, 12 tables) ✅ patterns.db created (155KB, 4 tables + FTS) ✅ All Phase 2 configs written successfully ✅ Complete initialization with no errors ## Phase 2 Features Confirmed Working - Learning System: Q-learning (lr=0.1, γ=0.95, 20% target) - Pattern Bank: 85% confidence, extraction enabled - Improvement Loop: 1hr cycles, A/B testing, manual approval ## Files Changed - .claude/agents/qe-quality-analyzer.md (NEW) - src/cli/commands/init.ts (MAJOR FIXES) - copyAgentTemplates(): Individual file copy, better logging - createBasicAgents(): All 17 agents - createMissingAgents(): Fixed file list bug - writeFleetConfig(): Added sanitization - sanitizeConfig(): NEW helper for undefined removal - src/learning/* (NEW - 9 files) - src/reasoning/* (NEW - 8 files) - tests/* (NEW - 30+ test files) - docs/* (NEW - 60+ documentation files) ## Breaking Changes None - all changes are internal improvements ## Migration No migration needed - initialization now works correctly 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
627 lines
19 KiB
TypeScript
627 lines
19 KiB
TypeScript
/**
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* Phase 2 Comprehensive Benchmark Suite
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*
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* Performance benchmarks with validation against Phase 2 requirements:
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* - Pattern lookup: <50ms p95
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* - Learning overhead: <10% additional time
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* - Pattern extraction: <5s for 100 files
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* - Memory usage: <100MB per project
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* - Throughput: 100+ operations/sec
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*
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* @module tests/benchmarks/phase2-benchmarks
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*/
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import { describe, it, expect, beforeEach, afterEach } from '@jest/globals';
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import { QEReasoningBank } from '../../src/reasoning/QEReasoningBank';
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import { LearningEngine } from '../../src/learning/LearningEngine';
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import { PatternExtractor } from '../../src/reasoning/PatternExtractor';
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interface BenchmarkResult {
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operation: string;
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iterations: number;
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totalDuration: number;
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avgDuration: number;
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minDuration: number;
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maxDuration: number;
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p50: number;
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p95: number;
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p99: number;
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throughput: number;
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}
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class BenchmarkRunner {
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static async run(
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name: string,
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operation: () => Promise<void>,
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iterations: number = 100
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): Promise<BenchmarkResult> {
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const measurements: number[] = [];
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// Warmup
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for (let i = 0; i < 10; i++) {
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await operation();
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}
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// Actual benchmark
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const startTime = performance.now();
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for (let i = 0; i < iterations; i++) {
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const start = performance.now();
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await operation();
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const duration = performance.now() - start;
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measurements.push(duration);
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}
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const totalDuration = performance.now() - startTime;
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// Calculate statistics
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const sorted = measurements.sort((a, b) => a - b);
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const result: BenchmarkResult = {
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operation: name,
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iterations,
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totalDuration,
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avgDuration: measurements.reduce((a, b) => a + b, 0) / measurements.length,
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minDuration: sorted[0],
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maxDuration: sorted[sorted.length - 1],
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p50: sorted[Math.floor(sorted.length * 0.5)],
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p95: sorted[Math.floor(sorted.length * 0.95)],
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p99: sorted[Math.floor(sorted.length * 0.99)],
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throughput: (iterations / totalDuration) * 1000 // ops/sec
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};
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return result;
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}
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static printResult(result: BenchmarkResult): void {
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console.log(`\n━━━ ${result.operation} ━━━`);
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console.log(`Iterations: ${result.iterations}`);
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console.log(`Total: ${result.totalDuration.toFixed(2)}ms`);
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console.log(`Average: ${result.avgDuration.toFixed(2)}ms`);
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console.log(`Min: ${result.minDuration.toFixed(2)}ms`);
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console.log(`Max: ${result.maxDuration.toFixed(2)}ms`);
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console.log(`P50: ${result.p50.toFixed(2)}ms`);
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console.log(`P95: ${result.p95.toFixed(2)}ms`);
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console.log(`P99: ${result.p99.toFixed(2)}ms`);
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console.log(`Throughput: ${result.throughput.toFixed(0)} ops/sec`);
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}
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}
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describe('Phase 2 Comprehensive Benchmarks', () => {
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let reasoningBank: QEReasoningBank;
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let learningEngine: LearningEngine;
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let patternExtractor: PatternExtractor;
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beforeEach(() => {
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reasoningBank = new QEReasoningBank();
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learningEngine = new LearningEngine();
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patternExtractor = new PatternExtractor();
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});
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afterEach(() => {
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if (learningEngine) learningEngine.clear();
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});
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// ===========================================================================
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// QEReasoningBank Benchmarks
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// ===========================================================================
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describe('QEReasoningBank Benchmarks', () => {
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beforeEach(async () => {
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// Seed 1000 patterns
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for (let i = 0; i < 1000; i++) {
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await reasoningBank.storePattern({
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id: `bench-pattern-${i}`,
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name: `Benchmark Pattern ${i}`,
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category: i % 2 === 0 ? 'unit' : 'integration',
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framework: i % 3 === 0 ? 'jest' : i % 3 === 1 ? 'mocha' : 'vitest',
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language: 'typescript',
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description: `Benchmark pattern ${i}`,
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template: `template-${i}`,
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applicability: {
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complexity: i % 3 === 0 ? 'low' : i % 3 === 1 ? 'medium' : 'high',
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context: [`ctx-${i % 20}`],
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constraints: []
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},
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metrics: {
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successRate: 0.7 + Math.random() * 0.3,
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usageCount: Math.floor(Math.random() * 100),
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averageQuality: 0.7 + Math.random() * 0.3,
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lastUsed: new Date()
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},
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tags: [`tag-${i % 50}`, `type-${i % 10}`],
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metadata: { benchmarkId: i }
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});
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}
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});
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it('Benchmark: Pattern lookup by ID', async () => {
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const result = await BenchmarkRunner.run(
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'Pattern Lookup by ID',
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async () => {
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const id = `bench-pattern-${Math.floor(Math.random() * 1000)}`;
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await reasoningBank.getPattern(id);
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},
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200
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);
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BenchmarkRunner.printResult(result);
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// Validate against requirements
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expect(result.p95).toBeLessThan(50); // <50ms p95
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expect(result.avgDuration).toBeLessThan(20);
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expect(result.throughput).toBeGreaterThan(50);
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});
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it('Benchmark: Pattern search with filters', async () => {
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const result = await BenchmarkRunner.run(
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'Pattern Search with Filters',
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async () => {
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await reasoningBank.findMatchingPatterns({
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framework: 'jest',
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language: 'typescript',
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tags: [`tag-${Math.floor(Math.random() * 50)}`],
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limit: 10
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});
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},
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200
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);
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BenchmarkRunner.printResult(result);
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expect(result.p95).toBeLessThan(50);
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expect(result.avgDuration).toBeLessThan(30);
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});
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it('Benchmark: Pattern metrics update', async () => {
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const result = await BenchmarkRunner.run(
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'Pattern Metrics Update',
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async () => {
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const id = `bench-pattern-${Math.floor(Math.random() * 1000)}`;
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await reasoningBank.updateMetrics(id, true, 0.9);
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},
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200
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);
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BenchmarkRunner.printResult(result);
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expect(result.p95).toBeLessThan(20);
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expect(result.throughput).toBeGreaterThan(100);
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});
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it('Benchmark: Concurrent pattern operations', async () => {
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const concurrency = 20;
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const start = performance.now();
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await Promise.all(
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Array.from({ length: concurrency }, async (_, i) => {
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// Mix of operations
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if (i % 3 === 0) {
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await reasoningBank.getPattern(`bench-pattern-${i}`);
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} else if (i % 3 === 1) {
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await reasoningBank.findMatchingPatterns({
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framework: 'jest',
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limit: 5
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});
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} else {
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await reasoningBank.updateMetrics(`bench-pattern-${i}`, true, 0.9);
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}
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})
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);
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const duration = performance.now() - start;
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const throughput = (concurrency / duration) * 1000;
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console.log(`\n━━━ Concurrent Pattern Operations ━━━`);
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console.log(`Concurrency: ${concurrency}`);
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console.log(`Total: ${duration.toFixed(2)}ms`);
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console.log(`Throughput: ${throughput.toFixed(0)} ops/sec`);
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expect(throughput).toBeGreaterThan(50);
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});
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});
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// ===========================================================================
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// LearningEngine Benchmarks
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// ===========================================================================
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describe('LearningEngine Benchmarks', () => {
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it('Benchmark: Record learning outcome', async () => {
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const result = await BenchmarkRunner.run(
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'Record Learning Outcome',
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async () => {
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await learningEngine.recordOutcome({
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id: `bench-rec-${Date.now()}-${Math.random()}`,
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timestamp: new Date(),
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testId: 'bench-test',
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testName: 'Benchmark Test',
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outcome: 'success',
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executionTime: 100,
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coverage: 0.9,
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edgeCasesCaught: 6,
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feedback: { quality: 0.85, relevance: 0.9 },
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metadata: {
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framework: 'jest',
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language: 'typescript',
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complexity: 2,
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linesOfCode: 100
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}
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});
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},
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200
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);
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BenchmarkRunner.printResult(result);
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// Should have <10ms overhead
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expect(result.avgDuration).toBeLessThan(10);
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expect(result.p95).toBeLessThan(20);
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expect(result.throughput).toBeGreaterThan(100);
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});
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it('Benchmark: Trend analysis with 1000 records', async () => {
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// Seed 1000 records
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for (let i = 0; i < 1000; i++) {
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await learningEngine.recordOutcome({
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id: `trend-${i}`,
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timestamp: new Date(Date.now() + i * 1000),
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testId: `test-${i}`,
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testName: `Test ${i}`,
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outcome: i % 10 === 0 ? 'flaky' : 'success',
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executionTime: 100 + (i % 100),
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coverage: 0.75 + (i % 100) * 0.002,
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edgeCasesCaught: 4 + (i % 10),
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feedback: { quality: 0.7 + (i % 100) * 0.003, relevance: 0.85 },
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metadata: {
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framework: 'jest',
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language: 'typescript',
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complexity: 2,
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linesOfCode: 100
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}
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});
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}
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const result = await BenchmarkRunner.run(
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'Trend Analysis (1000 records)',
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async () => {
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await learningEngine.analyzeTrends();
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},
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20
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);
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BenchmarkRunner.printResult(result);
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expect(result.avgDuration).toBeLessThan(500);
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expect(result.p95).toBeLessThan(1000);
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});
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it('Benchmark: Apply learning recommendations', async () => {
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// Seed data
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for (let i = 0; i < 50; i++) {
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await learningEngine.recordOutcome({
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id: `apply-${i}`,
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timestamp: new Date(),
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testId: `test-${i}`,
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testName: `Test ${i}`,
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outcome: 'success',
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executionTime: 100,
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coverage: 0.85,
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edgeCasesCaught: 6,
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feedback: { quality: 0.8, relevance: 0.85 },
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metadata: {
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framework: 'jest',
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language: 'typescript',
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complexity: 2,
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linesOfCode: 100
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}
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});
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}
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const result = await BenchmarkRunner.run(
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'Apply Learning Recommendations',
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async () => {
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await learningEngine.applyLearning({
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framework: 'jest',
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language: 'typescript',
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complexity: 2
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});
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},
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100
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);
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BenchmarkRunner.printResult(result);
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expect(result.avgDuration).toBeLessThan(50);
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expect(result.throughput).toBeGreaterThan(20);
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});
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it('Benchmark: Improvement metrics calculation', async () => {
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// Seed 30 days of data
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for (let i = 0; i < 90; i++) {
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await learningEngine.recordOutcome({
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id: `metrics-${i}`,
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timestamp: new Date(Date.now() - (90 - i) * 24 * 60 * 60 * 1000),
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testId: `test-${i}`,
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testName: `Test ${i}`,
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outcome: 'success',
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executionTime: 100,
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coverage: 0.8 + i * 0.001,
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edgeCasesCaught: 5 + Math.floor(i / 10),
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feedback: { quality: 0.75 + i * 0.002, relevance: 0.85 },
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metadata: {
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framework: 'jest',
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language: 'typescript',
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complexity: 2,
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linesOfCode: 100
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}
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});
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}
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const result = await BenchmarkRunner.run(
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'Improvement Metrics (30 days)',
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async () => {
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await learningEngine.getImprovementMetrics(30);
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},
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50
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);
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BenchmarkRunner.printResult(result);
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expect(result.avgDuration).toBeLessThan(100);
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});
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});
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// ===========================================================================
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// PatternExtractor Benchmarks
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// ===========================================================================
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describe('PatternExtractor Benchmarks', () => {
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const sampleCode = `
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describe('UserService', () => {
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let service: UserService;
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beforeEach(() => {
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service = new UserService();
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});
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it('should create user with valid data', async () => {
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const user = await service.createUser({
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email: 'test@example.com',
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name: 'Test User'
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});
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expect(user.id).toBeDefined();
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expect(user.email).toBe('test@example.com');
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});
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it('should throw on duplicate email', async () => {
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await service.createUser({ email: 'test@example.com', name: 'Test' });
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await expect(
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service.createUser({ email: 'test@example.com', name: 'Test2' })
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).rejects.toThrow('Email already exists');
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});
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});
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`;
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it('Benchmark: Pattern extraction from code', async () => {
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const result = await BenchmarkRunner.run(
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'Pattern Extraction',
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async () => {
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await patternExtractor.extractPatterns(sampleCode, {
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framework: 'jest',
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language: 'typescript'
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});
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},
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100
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);
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BenchmarkRunner.printResult(result);
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expect(result.avgDuration).toBeLessThan(100);
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expect(result.throughput).toBeGreaterThan(10);
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});
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it('Benchmark: Large file extraction (1000 lines)', async () => {
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const largeCode = Array.from({ length: 50 }, (_, i) => `
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describe('Feature ${i}', () => {
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it('test ${i}a', () => { expect(true).toBe(true); });
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it('test ${i}b', () => { expect(1 + 1).toBe(2); });
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it('test ${i}c', async () => {
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const result = await fetchData();
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expect(result).toBeDefined();
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});
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});
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`).join('\n');
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const result = await BenchmarkRunner.run(
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'Large File Extraction (1000 lines)',
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async () => {
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await patternExtractor.extractPatterns(largeCode, {
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framework: 'jest',
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language: 'typescript'
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});
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},
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20
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);
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BenchmarkRunner.printResult(result);
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expect(result.avgDuration).toBeLessThan(500);
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});
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it('Benchmark: Batch extraction (100 files)', async () => {
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const files = Array.from({ length: 100 }, (_, i) => ({
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code: sampleCode,
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options: { framework: 'jest' as const, language: 'typescript' as const }
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}));
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const start = performance.now();
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for (const file of files) {
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await patternExtractor.extractPatterns(file.code, file.options);
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}
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const duration = performance.now() - start;
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const throughput = (files.length / duration) * 1000;
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console.log(`\n━━━ Batch Pattern Extraction (100 files) ━━━`);
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console.log(`Total: ${duration.toFixed(2)}ms`);
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console.log(`Average per file: ${(duration / files.length).toFixed(2)}ms`);
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console.log(`Throughput: ${throughput.toFixed(1)} files/sec`);
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// Should complete in <5 seconds
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expect(duration).toBeLessThan(5000);
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});
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});
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// ===========================================================================
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// Memory Benchmarks
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// ===========================================================================
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describe('Memory Benchmarks', () => {
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it('Benchmark: Memory usage under load', async () => {
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if (global.gc) global.gc();
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const initialMemory = process.memoryUsage().heapUsed;
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// Simulate typical workload
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// 500 patterns + 1000 learning records + 100 extractions
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for (let i = 0; i < 500; i++) {
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await reasoningBank.storePattern({
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id: `mem-${i}`,
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name: `Pattern ${i}`,
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category: 'unit',
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framework: 'jest',
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language: 'typescript',
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description: 'Memory test',
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template: '...',
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applicability: { complexity: 'medium', context: [], constraints: [] },
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metrics: {
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successRate: 0.8,
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|
usageCount: 0,
|
|
averageQuality: 0,
|
|
lastUsed: new Date()
|
|
},
|
|
tags: [],
|
|
metadata: {}
|
|
});
|
|
}
|
|
|
|
for (let i = 0; i < 1000; i++) {
|
|
await learningEngine.recordOutcome({
|
|
id: `mem-rec-${i}`,
|
|
timestamp: new Date(),
|
|
testId: `test-${i}`,
|
|
testName: `Test ${i}`,
|
|
outcome: 'success',
|
|
executionTime: 100,
|
|
coverage: 0.85,
|
|
edgeCasesCaught: 6,
|
|
feedback: { quality: 0.8, relevance: 0.85 },
|
|
metadata: {
|
|
framework: 'jest',
|
|
language: 'typescript',
|
|
complexity: 2,
|
|
linesOfCode: 100
|
|
}
|
|
});
|
|
}
|
|
|
|
if (global.gc) global.gc();
|
|
|
|
const finalMemory = process.memoryUsage().heapUsed;
|
|
const memoryIncrease = (finalMemory - initialMemory) / (1024 * 1024);
|
|
|
|
console.log(`\n━━━ Memory Usage ━━━`);
|
|
console.log(`Initial: ${(initialMemory / 1024 / 1024).toFixed(2)}MB`);
|
|
console.log(`Final: ${(finalMemory / 1024 / 1024).toFixed(2)}MB`);
|
|
console.log(`Increase: ${memoryIncrease.toFixed(2)}MB`);
|
|
|
|
// Should be <100MB for typical workload
|
|
expect(memoryIncrease).toBeLessThan(100);
|
|
});
|
|
});
|
|
|
|
// ===========================================================================
|
|
// End-to-End Benchmarks
|
|
// ===========================================================================
|
|
|
|
describe('End-to-End Benchmarks', () => {
|
|
it('Benchmark: Complete workflow (extract → store → retrieve → learn)', async () => {
|
|
const sampleCode = `
|
|
describe('API', () => {
|
|
it('should handle requests', async () => {
|
|
const response = await api.get('/users');
|
|
expect(response.status).toBe(200);
|
|
});
|
|
});
|
|
`;
|
|
|
|
const result = await BenchmarkRunner.run(
|
|
'Complete Workflow',
|
|
async () => {
|
|
// 1. Extract patterns
|
|
const patterns = await patternExtractor.extractPatterns(sampleCode, {
|
|
framework: 'jest',
|
|
language: 'typescript'
|
|
});
|
|
|
|
// 2. Store patterns
|
|
for (const pattern of patterns) {
|
|
await reasoningBank.storePattern({
|
|
id: `e2e-${Date.now()}-${Math.random()}`,
|
|
name: pattern.name,
|
|
category: 'unit',
|
|
framework: 'jest',
|
|
language: 'typescript',
|
|
description: pattern.description,
|
|
template: pattern.template || '',
|
|
applicability: { complexity: 'medium', context: [], constraints: [] },
|
|
metrics: {
|
|
successRate: 0.9,
|
|
usageCount: 0,
|
|
averageQuality: 0,
|
|
lastUsed: new Date()
|
|
},
|
|
tags: pattern.tags || [],
|
|
metadata: {}
|
|
});
|
|
}
|
|
|
|
// 3. Retrieve patterns
|
|
await reasoningBank.findMatchingPatterns({
|
|
framework: 'jest',
|
|
language: 'typescript',
|
|
limit: 5
|
|
});
|
|
|
|
// 4. Record learning
|
|
await learningEngine.recordOutcome({
|
|
id: `e2e-${Date.now()}`,
|
|
timestamp: new Date(),
|
|
testId: 'e2e-test',
|
|
testName: 'E2E Test',
|
|
outcome: 'success',
|
|
executionTime: 100,
|
|
coverage: 0.9,
|
|
edgeCasesCaught: 6,
|
|
feedback: { quality: 0.85, relevance: 0.9 },
|
|
metadata: {
|
|
framework: 'jest',
|
|
language: 'typescript',
|
|
complexity: 2,
|
|
linesOfCode: 100
|
|
}
|
|
});
|
|
},
|
|
50
|
|
);
|
|
|
|
BenchmarkRunner.printResult(result);
|
|
|
|
// Complete workflow should be fast
|
|
expect(result.avgDuration).toBeLessThan(200);
|
|
expect(result.p95).toBeLessThan(500);
|
|
});
|
|
});
|
|
});
|