Files
Profa ec2c243172 fix(embeddings): complete 384-dim standardization across tests and providers
- Update default embed model from nomic-embed-text to all-MiniLM-L6-v2
  in Ollama LLM provider
- Fix 15 test files with hardcoded 768-dim references
- Update mock model names in Ollama health checks
- Update comments referencing old model name

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 12:33:47 +00:00

589 lines
18 KiB
TypeScript

/**
* Agentic QE v3 - Semantic Analyzer Service Unit Tests
*/
import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest';
import {
SemanticAnalyzerService,
SemanticAnalyzerConfig,
} from '../../../../src/domains/code-intelligence/services/semantic-analyzer';
import { MemoryBackend, VectorSearchResult } from '../../../../src/kernel/interfaces';
import { IEmbeddingProvider, EMBEDDING_CONFIG } from '../../../../src/shared/embeddings';
/**
* Mock Embedding Provider for testing
* Generates deterministic pseudo-embeddings without requiring Ollama
*/
function createMockEmbeddingProvider(): IEmbeddingProvider {
return {
async embed(text: string): Promise<number[]> {
// Generate deterministic embedding based on text content
const embedding = new Array(EMBEDDING_CONFIG.DIMENSIONS).fill(0);
for (let i = 0; i < text.length && i < embedding.length; i++) {
embedding[i] = text.charCodeAt(i) / 1000;
}
// Normalize
const magnitude = Math.sqrt(embedding.reduce((sum, v) => sum + v * v, 0)) || 1;
return embedding.map((v) => v / magnitude);
},
async healthCheck(): Promise<boolean> {
return true;
},
getDimensions(): number {
return EMBEDDING_CONFIG.DIMENSIONS;
},
};
}
/**
* Mock Memory Backend for testing
*/
function createMockMemoryBackend(): MemoryBackend {
const storage = new Map<string, unknown>();
const vectors = new Map<string, { embedding: number[]; metadata: unknown }>();
return {
initialize: vi.fn().mockResolvedValue(undefined),
dispose: vi.fn().mockResolvedValue(undefined),
set: vi.fn(async (key: string, value: unknown) => {
storage.set(key, value);
}),
get: vi.fn(async <T>(key: string): Promise<T | undefined> => {
return storage.get(key) as T | undefined;
}),
delete: vi.fn(async (key: string): Promise<boolean> => {
return storage.delete(key);
}),
has: vi.fn(async (key: string): Promise<boolean> => {
return storage.has(key);
}),
search: vi.fn(async (pattern: string, limit?: number): Promise<string[]> => {
const regex = new RegExp(pattern.replace(/\*/g, '.*'));
const matches: string[] = [];
for (const key of storage.keys()) {
if (regex.test(key)) {
matches.push(key);
if (limit && matches.length >= limit) break;
}
}
return matches;
}),
vectorSearch: vi.fn(async (_embedding: number[], k: number): Promise<VectorSearchResult[]> => {
const results: VectorSearchResult[] = [];
let count = 0;
for (const [key, data] of vectors.entries()) {
if (count >= k) break;
results.push({
key,
score: 0.95 - count * 0.05,
metadata: data.metadata,
});
count++;
}
return results;
}),
storeVector: vi.fn(async (key: string, embedding: number[], metadata?: unknown) => {
vectors.set(key, { embedding, metadata });
}),
};
}
describe('SemanticAnalyzerService', () => {
let service: SemanticAnalyzerService;
let mockMemory: MemoryBackend;
let mockEmbeddingProvider: IEmbeddingProvider;
beforeEach(() => {
mockMemory = createMockMemoryBackend();
mockEmbeddingProvider = createMockEmbeddingProvider();
// Use mock embedding provider to avoid Ollama dependency in tests
service = new SemanticAnalyzerService(mockMemory, {
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false, // Disable Nomic to use mock provider
});
});
afterEach(() => {
vi.restoreAllMocks();
});
describe('search', () => {
beforeEach(async () => {
// Pre-index some code
await service.indexCode('src/utils.ts', `
export function calculateSum(a: number, b: number): number {
return a + b;
}
`);
await service.indexCode('src/math.ts', `
export class MathOperations {
add(x: number, y: number) { return x + y; }
subtract(x: number, y: number) { return x - y; }
}
`);
});
it('should perform semantic search and return results', async () => {
const result = await service.search({
query: 'function that adds numbers',
type: 'semantic',
limit: 5,
});
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.searchTime).toBeGreaterThanOrEqual(0);
expect(result.value.total).toBeGreaterThanOrEqual(0);
}
});
it('should perform exact search for literal matches', async () => {
await service.indexCode('src/test.ts', 'const exactMatch = "findMe";');
const result = await service.search({
query: 'findMe',
type: 'exact',
limit: 10,
});
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.results.length).toBeGreaterThanOrEqual(0);
}
});
it('should perform fuzzy search for approximate matches', async () => {
await service.indexCode('src/handler.ts', 'function handleUserRequest() {}');
const result = await service.search({
query: 'handle user',
type: 'fuzzy',
limit: 10,
});
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.results).toBeDefined();
}
});
it('should filter results by scope', async () => {
await service.indexCode('src/api/routes.ts', 'export const routes = [];');
await service.indexCode('lib/helpers.ts', 'export const helpers = [];');
const result = await service.search({
query: 'export',
type: 'exact',
scope: ['src/api'],
limit: 10,
});
expect(result.success).toBe(true);
});
it('should apply search filters', async () => {
await service.indexCode('src/big-file.ts', 'x'.repeat(1000));
const result = await service.search({
query: 'code',
type: 'semantic',
filters: [{ field: 'size', operator: 'gt', value: 500 }],
limit: 10,
});
expect(result.success).toBe(true);
});
it('should return error for unknown search type', async () => {
const result = await service.search({
query: 'test',
// @ts-expect-error - testing invalid type
type: 'invalid',
limit: 10,
});
expect(result.success).toBe(false);
});
it('should respect result limit', async () => {
// Index multiple files
for (let i = 0; i < 20; i++) {
await service.indexCode(`src/file${i}.ts`, `const value${i} = ${i};`);
}
const result = await service.search({
query: 'const',
type: 'exact',
limit: 5,
});
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.results.length).toBeLessThanOrEqual(5);
}
});
});
describe('indexCode', () => {
it('should index code content successfully', async () => {
const result = await service.indexCode(
'src/service.ts',
'export class UserService { getUser() { return null; } }'
);
expect(result.success).toBe(true);
expect(mockMemory.storeVector).toHaveBeenCalled();
expect(mockMemory.set).toHaveBeenCalled();
});
it('should generate embeddings for indexed code', async () => {
await service.indexCode('src/test.ts', 'const test = "value";');
expect(mockMemory.storeVector).toHaveBeenCalledWith(
expect.stringContaining('code-intelligence:semantic:code'),
expect.any(Array),
expect.objectContaining({
file: 'src/test.ts',
})
);
});
it('should extract and store code metadata', async () => {
const code = `
export class TestClass {
async fetchData() {
return fetch('/api');
}
}
`;
await service.indexCode('src/test-class.ts', code);
expect(mockMemory.set).toHaveBeenCalledWith(
expect.stringContaining('content'),
expect.objectContaining({
file: 'src/test-class.ts',
metadata: expect.objectContaining({
hasClasses: true,
}),
}),
expect.any(Object)
);
});
it('should handle indexing errors gracefully', async () => {
const errorMemory = createMockMemoryBackend();
errorMemory.storeVector = vi.fn().mockRejectedValue(new Error('Storage failed'));
const errorService = new SemanticAnalyzerService(errorMemory, {
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false,
});
const result = await errorService.indexCode('src/error.ts', 'code');
expect(result.success).toBe(false);
});
});
describe('findSimilar', () => {
beforeEach(async () => {
await service.indexCode('src/add.ts', 'function add(a, b) { return a + b; }');
await service.indexCode('src/sum.ts', 'const sum = (x, y) => x + y;');
});
it('should find semantically similar code', async () => {
const result = await service.findSimilar(
'function addition(x, y) { return x + y; }',
5
);
expect(result.success).toBe(true);
if (result.success) {
expect(Array.isArray(result.value)).toBe(true);
}
});
it('should filter results below minimum score threshold', async () => {
const lowScoreMemory = createMockMemoryBackend();
lowScoreMemory.vectorSearch = vi.fn().mockResolvedValue([
{ key: 'k1', score: 0.3, metadata: { file: 'f1.ts' } }, // Below threshold
{ key: 'k2', score: 0.8, metadata: { file: 'f2.ts' } }, // Above threshold
]);
const lowScoreService = new SemanticAnalyzerService(lowScoreMemory, {
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false,
});
await lowScoreService.indexCode('f2.ts', 'code');
const result = await lowScoreService.findSimilar('test code', 10);
expect(result.success).toBe(true);
if (result.success) {
// Results with score < 0.5 (default minScore) should be filtered
for (const r of result.value) {
expect(r.score).toBeGreaterThanOrEqual(0.5);
}
}
});
it('should return code snippets with highlights', async () => {
const result = await service.findSimilar('function add', 3);
expect(result.success).toBe(true);
if (result.success && result.value.length > 0) {
expect(result.value[0]).toHaveProperty('snippet');
expect(result.value[0]).toHaveProperty('highlights');
}
});
it('should handle empty results gracefully', async () => {
const emptyMemory = createMockMemoryBackend();
emptyMemory.vectorSearch = vi.fn().mockResolvedValue([]);
const emptyService = new SemanticAnalyzerService(emptyMemory, {
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false,
});
const result = await emptyService.findSimilar('unique code', 5);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value).toEqual([]);
}
});
});
describe('analyze', () => {
it('should extract programming concepts from code', async () => {
const code = `
export async function processData(items: Item[]): Promise<Result[]> {
return items.map(item => transform(item));
}
`;
const result = await service.analyze(code);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.concepts).toContain('asynchronous');
expect(result.value.concepts).toContain('modular');
expect(result.value.concepts).toContain('collection-processing');
}
});
it('should detect design patterns', async () => {
const singletonCode = `
class Database {
private static instance: Database;
static getInstance(): Database {
if (!this.instance) {
this.instance = new Database();
}
return this.instance;
}
}
`;
const result = await service.analyze(singletonCode);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.patterns).toContain('singleton');
}
});
it('should calculate cyclomatic complexity', async () => {
const complexCode = `
function process(x) {
if (x > 0) {
if (x > 10) {
return 'large';
} else {
return 'medium';
}
} else if (x === 0) {
return 'zero';
} else {
return 'negative';
}
}
`;
const result = await service.analyze(complexCode);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.complexity.cyclomatic).toBeGreaterThan(1);
}
});
it('should calculate cognitive complexity', async () => {
const nestedCode = `
function nested(a, b, c) {
if (a) {
for (let i = 0; i < 10; i++) {
if (b) {
while (c) {
// deeply nested
}
}
}
}
}
`;
const result = await service.analyze(nestedCode);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.complexity.cognitive).toBeGreaterThan(0);
}
});
it('should calculate Halstead metrics', async () => {
const code = `
function calculate(a, b, c) {
const sum = a + b;
const product = sum * c;
return product / 2;
}
`;
const result = await service.analyze(code);
expect(result.success).toBe(true);
if (result.success) {
const halstead = result.value.complexity.halstead;
expect(halstead).toHaveProperty('vocabulary');
expect(halstead).toHaveProperty('length');
expect(halstead).toHaveProperty('difficulty');
expect(halstead).toHaveProperty('effort');
expect(halstead).toHaveProperty('time');
expect(halstead).toHaveProperty('bugs');
}
});
it('should extract dependencies from imports', async () => {
const code = `
import { useState } from 'react';
import axios from 'axios';
const fs = require('fs');
`;
const result = await service.analyze(code);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.dependencies).toContain('react');
expect(result.value.dependencies).toContain('axios');
expect(result.value.dependencies).toContain('fs');
}
});
it('should generate improvement suggestions', async () => {
// Code with high complexity and no error handling
const code = `
async function complexFunction(a, b, c, d, e, f) {
if (a) { if (b) { if (c) { if (d) { if (e) { if (f) {
return Promise.resolve('deep');
}}}}}}
return a || b || c || d || e || f;
}
`.repeat(10);
const result = await service.analyze(code);
expect(result.success).toBe(true);
if (result.success) {
expect(result.value.suggestions.length).toBeGreaterThan(0);
}
});
it('should use cache for repeated analysis', async () => {
const code = 'const cached = "test";';
// First analysis
await service.analyze(code);
// Second analysis (should use cache)
const result = await service.analyze(code);
expect(result.success).toBe(true);
});
});
describe('getEmbedding', () => {
it('should generate embedding vector of correct dimension', async () => {
const embedding = await service.getEmbedding('test code');
expect(Array.isArray(embedding)).toBe(true);
expect(embedding.length).toBe(EMBEDDING_CONFIG.DIMENSIONS); // 384 for all-MiniLM-L6-v2
});
it('should generate normalized embeddings', async () => {
const embedding = await service.getEmbedding('normalize test');
// Check magnitude is approximately 1 (normalized)
const magnitude = Math.sqrt(embedding.reduce((sum, v) => sum + v * v, 0));
expect(magnitude).toBeCloseTo(1, 5);
});
it('should cache embeddings when caching is enabled', async () => {
const code = 'const cacheTest = 1;';
const embedding1 = await service.getEmbedding(code);
const embedding2 = await service.getEmbedding(code);
expect(embedding1).toEqual(embedding2);
});
it('should generate different embeddings for different code', async () => {
const embedding1 = await service.getEmbedding('function add(a, b) { return a + b; }');
const embedding2 = await service.getEmbedding('class User { constructor(name) { this.name = name; } }');
// Embeddings should be different
expect(embedding1).not.toEqual(embedding2);
});
});
describe('configuration', () => {
it('should use custom configuration', () => {
const customConfig: Partial<SemanticAnalyzerConfig> = {
embeddingDimension: 512,
minScore: 0.7,
maxResults: 50,
enableCaching: false,
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false,
};
const customService = new SemanticAnalyzerService(mockMemory, customConfig);
expect(customService).toBeDefined();
});
it('should respect minScore filter in search', async () => {
const strictMemory = createMockMemoryBackend();
strictMemory.vectorSearch = vi.fn().mockResolvedValue([
{ key: 'low', score: 0.3, metadata: { file: 'low.ts' } },
{ key: 'high', score: 0.9, metadata: { file: 'high.ts' } },
]);
const strictService = new SemanticAnalyzerService(strictMemory, {
minScore: 0.8,
embeddingProvider: mockEmbeddingProvider,
useNomicEmbeddings: false,
});
await strictService.indexCode('high.ts', 'code');
const result = await strictService.findSimilar('query', 10);
expect(result.success).toBe(true);
if (result.success) {
// Only results above minScore should be returned
expect(result.value.every(r => r.score >= 0.8)).toBe(true);
}
});
});
});