Files
proffesor-for-testing__agen…/tests/unit/agents/NeuralCapableMixin.test.ts
Profa a80fec1be9 feat: Phase 3 Advanced Features - QUIC + Neural Training (Prototype)
## Summary
Phase 3 implementation complete with QUIC transport and Neural training as prototype.
Performance targets MET (67.7% faster), but critical issues prevent production deployment.

## Components Added

### QUIC Transport (4 files, ~2,300 LOC)
- src/types/quic.ts - Type definitions
- src/core/transport/QUICTransport.ts - Transport layer
- src/core/memory/AgentDBIntegration.ts - Memory integration
- src/agents/mixins/QUICCapableMixin.ts - Agent integration

### Neural Training (4 files, ~2,300 LOC)
- src/learning/NeuralPatternMatcher.ts - Neural network
- src/learning/NeuralTrainer.ts - Training pipeline
- src/agents/mixins/NeuralCapableMixin.ts - Agent integration
- config/neural-agent.config.ts - Configuration

### Agent Updates (3 files, ~420 LOC)
- src/agents/BaseAgent.ts - QUIC + Neural support
- src/agents/TestGeneratorAgent.ts - Neural predictions
- src/core/memory/SwarmMemoryManager.ts - QUIC integration

### Tests (13 files, ~5,100 LOC)
- QUIC: 106 tests (56 passing, 50 infrastructure issues)
- Neural: 68 tests (55 passing, 13 accuracy issues)
- Coverage: 0.59% (infrastructure prevents proper collection)

### Documentation (21 files, ~15,000 lines)
- Complete architecture documentation
- 30+ architectural diagrams
- Comprehensive usage guides
- Code review reports
- Performance benchmarks

### Configuration
- .agentic-qe/config/fleet.json - Fixed agents array (5 agents)
- .agentic-qe/config/transport.json - QUIC configuration
- .agentic-qe/config/routing.json - Phase 3 feature flags

## Performance Results

✅ QUIC Transport (TARGETS EXCEEDED):
- 67.7% faster than TCP (target: 50-70%)
- 6.23ms connection time (target: <50ms)
- 2.03ms message latency (target: <100ms)

⚠️ Neural Training (BELOW TARGET):
- 65% accuracy (target: 85%)
- <100ms prediction time (target: <100ms) ✅
- <1s training time (target: <5s) ✅

❌ Test Coverage (CRITICAL GAP):
- 0.59% coverage (target: 80%)
- Infrastructure issues prevent proper test execution

## Critical Issues (BLOCKERS)

🔴 Security Vulnerabilities:
1. Self-signed certificates in production code
2. Disabled certificate validation (rejectUnauthorized: false)

🟡 Implementation Issues:
3. QUIC not actually implemented (UDP only, not real QUIC protocol)
4. Neural accuracy insufficient (65% vs 85%)
5. Memory leaks in resource cleanup

## Status

Phase 3 Status: 🟡 PROTOTYPE COMPLETE - NOT PRODUCTION READY

Production Readiness: 70%
- Phase 1-2: 100% stable, 86% test pass rate ✅
- Phase 3: 70% prototype, requires 5-6 weeks hardening ⚠️

## Feature Flags (DISABLED BY DEFAULT)

All Phase 3 features are opt-in:
- quicEnabled: false (default)
- neuralEnabled: false (default)
- Zero impact on existing functionality

## Recommendation

⭐ POSTPONE PHASE 3:
- Ship stable Phase 1-2 now
- Gather user feedback
- Revisit Phase 3 based on actual needs

OR allocate 5-6 weeks with 2-3 engineers for production hardening.

## Files Changed
- Added: 32 source files (~11,000 LOC)
- Added: 13 test files (~5,100 LOC)
- Added: 21 documentation files (~15,000 lines)
- Updated: 4 configuration files
- Updated: 3 agent files

Total: 73 files, +31,100 insertions

🤖 Generated with Agentic QE Fleet v1.1.0
Phase 3 Swarm: 11 specialized agents (system-architect, backend-dev, ml-developer, coder x3, tester x2, qe-coverage-analyzer, reviewer)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-20 16:02:52 +00:00

342 lines
10 KiB
TypeScript

/**
* Tests for NeuralCapableMixin
*
* Validates neural pattern matching, prediction, caching, and error handling.
*/
import {
DefaultNeuralMatcher,
createNeuralMatcher,
safeNeuralPredict,
mergeWithNeuralPrediction,
getNeuralMetrics,
NeuralInput,
NeuralConfig,
DEFAULT_NEURAL_CONFIG
} from '../../../src/agents/mixins/NeuralCapableMixin';
describe('NeuralCapableMixin', () => {
describe('DefaultNeuralMatcher', () => {
let matcher: DefaultNeuralMatcher;
beforeEach(() => {
matcher = new DefaultNeuralMatcher({ enabled: true });
});
test('should initialize with default config', () => {
const status = matcher.getStatus();
expect(status.available).toBe(true);
expect(status.predictions).toBe(0);
});
test('should make flakiness predictions', async () => {
const input: NeuralInput = {
type: 'flakiness',
data: {
testName: 'test_example',
results: [
{ testName: 'test_example', duration: 100, passed: true, timestamp: new Date() },
{ testName: 'test_example', duration: 120, passed: false, timestamp: new Date() },
{ testName: 'test_example', duration: 110, passed: true, timestamp: new Date() },
{ testName: 'test_example', duration: 105, passed: true, timestamp: new Date() },
{ testName: 'test_example', duration: 115, passed: false, timestamp: new Date() }
]
}
};
const prediction = await matcher.predict(input);
expect(prediction).toBeDefined();
expect(prediction).not.toBeNull();
expect(prediction.result).toBeDefined();
expect(prediction.confidence).toBeGreaterThan(0);
expect(prediction.confidence).toBeLessThanOrEqual(1);
expect(typeof prediction.result.isFlaky).toBe('boolean');
expect(prediction.result.confidence).toBeGreaterThan(0);
expect(prediction.timestamp).toBeInstanceOf(Date);
expect(prediction.reasoning).toBeInstanceOf(Array);
expect(prediction.reasoning.length).toBeGreaterThan(0);
});
test('should make test generation predictions', async () => {
const input: NeuralInput = {
type: 'test-generation',
data: {
codeSignature: { functionName: 'calculateSum' },
framework: 'jest'
}
};
const prediction = await matcher.predict(input);
expect(prediction).toBeDefined();
expect(prediction.result).toHaveProperty('suggestedTests');
expect(prediction.result.suggestedTests).toBeInstanceOf(Array);
expect(prediction.confidence).toBeGreaterThan(0.7);
});
test('should make coverage gap predictions', async () => {
const input: NeuralInput = {
type: 'coverage-gap',
data: {
currentCoverage: 0.65,
codebase: { files: [] }
}
};
const prediction = await matcher.predict(input);
expect(prediction).toBeDefined();
expect(prediction.result).toHaveProperty('gaps');
expect(prediction.result.gaps).toBeInstanceOf(Array);
});
test('should make risk score predictions', async () => {
const input: NeuralInput = {
type: 'risk-score',
data: {
changes: [],
historicalData: {}
}
};
const prediction = await matcher.predict(input);
expect(prediction).toBeDefined();
expect(prediction.result).toHaveProperty('riskScore');
expect(prediction.result.riskLevel).toMatch(/LOW|MEDIUM|HIGH|CRITICAL/);
});
test('should cache predictions', async () => {
const input: NeuralInput = {
type: 'test-generation',
data: { codeSignature: {}, framework: 'jest' }
};
// First prediction
const pred1 = await matcher.predict(input);
const status1 = matcher.getStatus();
// Second prediction (should be cached)
const pred2 = await matcher.predict(input);
const status2 = matcher.getStatus();
expect(pred1.confidence).toBe(pred2.confidence);
expect(status2.cacheHitRate).toBeGreaterThan(status1.cacheHitRate);
});
test('should respect cache TTL', async () => {
const shortCacheMatcher = new DefaultNeuralMatcher({
enabled: true,
cacheTTL: 100 // 100ms
});
const input: NeuralInput = {
type: 'test-generation',
data: { codeSignature: {}, framework: 'jest' }
};
// First prediction
await shortCacheMatcher.predict(input);
// Wait for cache to expire
await new Promise(resolve => setTimeout(resolve, 150));
// Should generate new prediction
const pred2 = await shortCacheMatcher.predict(input);
expect(pred2).toBeDefined();
});
test('should handle fallback on errors', async () => {
const matcher = new DefaultNeuralMatcher({
enabled: true,
fallbackEnabled: true
});
const input: NeuralInput = {
type: 'test-generation' as any,
data: null // Invalid data to trigger error
};
const prediction = await matcher.predict(input);
expect(prediction).toBeDefined();
expect(prediction.confidence).toBe(0.5); // Fallback confidence
expect(prediction.reasoning).toContain('Neural prediction unavailable');
});
});
describe('createNeuralMatcher', () => {
test('should create matcher when enabled', () => {
const matcher = createNeuralMatcher({ enabled: true });
expect(matcher).not.toBeNull();
expect(matcher?.isAvailable()).toBe(true);
});
test('should return null when disabled', () => {
const matcher = createNeuralMatcher({ enabled: false });
expect(matcher).toBeNull();
});
test('should apply custom configuration', () => {
const config: Partial<NeuralConfig> = {
enabled: true,
confidence: 0.85,
cacheEnabled: false
};
const matcher = createNeuralMatcher(config);
expect(matcher).not.toBeNull();
});
});
describe('safeNeuralPredict', () => {
test('should return null for null matcher', async () => {
const result = await safeNeuralPredict(null, {} as NeuralInput);
expect(result).toBeNull();
});
test('should return null for unavailable matcher', async () => {
const matcher = createNeuralMatcher({ enabled: false });
const result = await safeNeuralPredict(matcher, {} as NeuralInput);
expect(result).toBeNull();
});
test('should return prediction for valid matcher', async () => {
const matcher = createNeuralMatcher({ enabled: true });
const input: NeuralInput = {
type: 'test-generation',
data: { codeSignature: {}, framework: 'jest' }
};
const result = await safeNeuralPredict(matcher, input);
expect(result).not.toBeNull();
expect(result?.confidence).toBeGreaterThan(0);
});
test('should handle prediction errors gracefully', async () => {
const matcher = new DefaultNeuralMatcher({ enabled: true, fallbackEnabled: false });
// Mock predict to throw error
jest.spyOn(matcher, 'predict').mockRejectedValue(new Error('Test error'));
const input: NeuralInput = {
type: 'test-generation',
data: {}
};
const result = await safeNeuralPredict(matcher, input);
expect(result).toBeNull(); // Should return null on error
});
});
describe('mergeWithNeuralPrediction', () => {
test('should return traditional result when no neural prediction', () => {
const traditional = { value: 42 };
const merged = mergeWithNeuralPrediction(traditional, null);
expect(merged).toEqual({ value: 42 });
});
test('should include neural prediction in result', () => {
const traditional = { value: 42 };
const neural = {
result: { suggestedValue: 50 },
confidence: 0.8,
timestamp: new Date()
};
const merged = mergeWithNeuralPrediction(traditional, neural);
expect(merged.value).toBe(42);
expect(merged.neural).toBeDefined();
expect(merged.neural?.confidence).toBe(0.8);
});
test('should prefer neural with high confidence in neural-first strategy', () => {
const traditional = { value: 42 };
const neural = {
result: { value: 50 },
confidence: 0.9,
timestamp: new Date()
};
const merged = mergeWithNeuralPrediction(traditional, neural, 'neural-first');
expect(merged.value).toBe(50); // Neural value used
expect(merged.neural).toBeDefined();
});
});
describe('getNeuralMetrics', () => {
test('should return disabled metrics for null matcher', () => {
const metrics = getNeuralMetrics(null);
expect(metrics.enabled).toBe(false);
expect(metrics.predictions).toBe(0);
expect(metrics.avgConfidence).toBe(0);
expect(metrics.cacheHitRate).toBe(0);
});
test('should return metrics for active matcher', async () => {
const matcher = createNeuralMatcher({ enabled: true });
// Make some predictions
const input: NeuralInput = {
type: 'test-generation',
data: { codeSignature: {}, framework: 'jest' }
};
await matcher?.predict(input);
await matcher?.predict(input); // Cached
const metrics = getNeuralMetrics(matcher);
expect(metrics.enabled).toBe(true);
expect(metrics.predictions).toBeGreaterThan(0);
expect(metrics.cacheHitRate).toBeGreaterThan(0);
});
});
describe('Integration Tests', () => {
test('should work in complete workflow', async () => {
// Create matcher
const matcher = createNeuralMatcher({
enabled: true,
confidence: 0.75,
cacheEnabled: true
});
expect(matcher).not.toBeNull();
// Make prediction
const input: NeuralInput = {
type: 'test-generation',
data: {
codeSignature: { functionName: 'processData' },
framework: 'jest',
complexity: { cyclomaticComplexity: 5 }
}
};
const prediction = await safeNeuralPredict(matcher, input);
expect(prediction).not.toBeNull();
expect(prediction?.confidence).toBeGreaterThan(0.7);
// Merge with traditional analysis
const traditional = { testsGenerated: 10 };
const merged = mergeWithNeuralPrediction(traditional, prediction, 'weighted');
expect(merged.testsGenerated).toBe(10);
expect(merged.neural).toBeDefined();
// Get metrics
const metrics = getNeuralMetrics(matcher);
expect(metrics.enabled).toBe(true);
expect(metrics.predictions).toBeGreaterThan(0);
});
});
});