---
name: moai-workflow-jit-docs/optimization
description: Performance optimization for JIT documentation, indexing, caching, and memory management
---

# JIT Documentation Optimization (v5.0.0)

## Memory-Efficient Caching

### 1. LRU Cache with Size Limits

```typescript
interface CacheEntry<T> {
 value: T;
 size: number;
 timestamp: number;
 accessCount: number;
}

class LRUDocumentCache<T> {
 private cache: Map<string, CacheEntry<T>> = new Map();
 private maxSize: number; // bytes
 private currentSize: number = 0;

 constructor(maxSizeInMB: number = 100) {
 this.maxSize = maxSizeInMB * 1024 * 1024;
 }

 set(key: string, value: T, sizeEstimate: number) {
 // Remove existing entry if present
 if (this.cache.has(key)) {
 const existing = this.cache.get(key)!;
 this.currentSize -= existing.size;
 }

 // Evict LRU items if necessary
 while (this.currentSize + sizeEstimate > this.maxSize && this.cache.size > 0) {
 this.evictLRU();
 }

 // Add new entry
 this.cache.set(key, {
 value,
 size: sizeEstimate,
 timestamp: Date.now(),
 accessCount: 0
 });

 this.currentSize += sizeEstimate;
 }

 get(key: string): T | undefined {
 const entry = this.cache.get(key);
 if (!entry) return undefined;

 // Update access tracking
 entry.accessCount++;
 entry.timestamp = Date.now();

 return entry.value;
 }

 private evictLRU() {
 // Find least recently used item
 let lruKey: string | null = null;
 let lruScore = Infinity;

 for (const [key, entry] of this.cache.entries()) {
 const score = entry.timestamp + (entry.accessCount * 1000);
 if (score < lruScore) {
 lruScore = score;
 lruKey = key;
 }
 }

 if (lruKey) {
 const removed = this.cache.get(lruKey)!;
 this.currentSize -= removed.size;
 this.cache.delete(lruKey);
 }
 }

 getStats() {
 return {
 items: this.cache.size,
 usedBytes: this.currentSize,
 usedMB: (this.currentSize / 1024 / 1024).toFixed(2),
 maxMB: (this.maxSize / 1024 / 1024).toFixed(2),
 hitRate: this.calculateHitRate()
 };
 }
}
```

## Index Optimization

### 1. Incremental Indexing

```typescript
class IncrementalDocumentIndex {
 private index: Map<string, Set<string>> = new Map(); // word -> docIds
 private docHashes: Map<string, string> = new Map(); // docId -> contentHash

 async indexDocuments(docs: DocumentContent[]): Promise<void> {
 for (const doc of docs) {
 const hash = this.calculateHash(doc.content);
 const previousHash = this.docHashes.get(doc.id);

 // Only reindex if content changed
 if (previousHash !== hash) {
 await this.indexDocument(doc);
 this.docHashes.set(doc.id, hash);
 }
 }
 }

 private async indexDocument(doc: DocumentContent) {
 // Extract and tokenize content
 const tokens = this.tokenize(doc.content);

 for (const token of new Set(tokens)) {
 if (!this.index.has(token)) {
 this.index.set(token, new Set());
 }

 this.index.get(token)!.add(doc.id);
 }
 }

 async search(query: string): Promise<string[]> {
 const tokens = this.tokenize(query);

 // Find intersection of document sets
 let results = this.index.get(tokens[0]) || new Set<string>();

 for (let i = 1; i < tokens.length; i++) {
 const tokenDocs = this.index.get(tokens[i]) || new Set();
 results = new Set([...results].filter(id => tokenDocs.has(id)));
 }

 return Array.from(results);
 }

 private tokenize(text: string): string[] {
 return text
 .toLowerCase()
 .match(/\b\w+\b/g) || [];
 }

 private calculateHash(content: string): string {
 return require('crypto')
 .createHash('sha256')
 .update(content)
 .digest('hex');
 }
}
```

## Compression and Storage

### 1. Content Compression

```typescript
import zlib from 'zlib';
import brotli from 'brotli';

class CompressedDocumentStorage {
 async compressDocument(doc: DocumentContent): Promise<CompressedDoc> {
 const json = JSON.stringify(doc);

 // Compress with brotli (better compression)
 const compressed = await this.brotliCompress(json);

 return {
 id: doc.id,
 compressed: compressed.toString('base64'),
 originalSize: Buffer.byteLength(json),
 compressedSize: compressed.length,
 compressionRatio: (compressed.length / Buffer.byteLength(json) * 100).toFixed(1) + '%'
 };
 }

 private async brotliCompress(data: string): Promise<Buffer> {
 return new Promise((resolve, reject) => {
 brotli.compress(Buffer.from(data), (err, output) => {
 if (err) reject(err);
 else resolve(output);
 });
 });
 }

 async decompressDocument(compressed: CompressedDoc): Promise<DocumentContent> {
 const buffer = Buffer.from(compressed.compressed, 'base64');

 return new Promise((resolve, reject) => {
 brotli.decompress(buffer, (err, output) => {
 if (err) reject(err);
 else resolve(JSON.parse(output.toString()));
 });
 });
 }
}
```

## Performance Monitoring

### 1. Load Time Metrics

```typescript
class DocumentLoadMetrics {
 async trackLoadTime(docId: string, stage: 'fetch' | 'parse' | 'enhance' | 'render') {
 const startTime = performance.now();

 try {
 const result = await this.loadDocument(docId);

 const duration = performance.now() - startTime;

 // Log metrics
 logger.info('Document load', {
 doc_id: docId,
 stage,
 duration_ms: duration,
 cache_hit: this.wasCacheHit,
 timestamp: new Date()
 });

 // Alert if slow
 if (duration > 1000) {
 metrics.increment('doc.load.slow', { stage });
 logger.warn('Slow document load', { docId, stage, duration });
 }

 return result;
 } catch (error) {
 metrics.increment('doc.load.error', { stage });
 logger.error('Document load failed', { docId, stage, error });
 throw error;
 }
 }

 // Performance budgets
 validatePerformanceBudget(stage: string, duration: number): boolean {
 const budgets = {
 'fetch': 500, // 500ms
 'parse': 200, // 200ms
 'enhance': 1000, // 1s
 'render': 300 // 300ms
 };

 const budget = budgets[stage as keyof typeof budgets];
 return duration <= budget;
 }
}
```

### 2. Memory Usage Monitoring

```typescript
class MemoryMonitor {
 trackMemoryUsage() {
 const memUsage = process.memoryUsage();

 metrics.gauge('memory.heapUsed', memUsage.heapUsed / 1024 / 1024); // MB
 metrics.gauge('memory.heapTotal', memUsage.heapTotal / 1024 / 1024);
 metrics.gauge('memory.external', memUsage.external / 1024 / 1024);

 // Alert if heap usage > 80%
 const heapUsagePercent = (memUsage.heapUsed / memUsage.heapTotal) * 100;
 if (heapUsagePercent > 80) {
 logger.warn('High memory usage', {
 heapUsagePercent: heapUsagePercent.toFixed(1)
 });

 // Trigger garbage collection
 if (global.gc) {
 global.gc();
 }
 }
 }
}
```

---

Version: 5.0.0 | Last Updated: 2025-11-22 | Enterprise Ready:
