# Performance Audit Report

**Branch**: feature/v0.3.1-quick-wins
**Base**: main
**Date**: 2025-11-17 20:20:00
**Files Analyzed**: 7
**Lines Changed**: +842, -56 (net +786)
**Commits**: 2

---

## Executive Summary

**Performance Score**: 8.5/10

**Merge Recommendation**: ✅ APPROVED WITH CONDITIONS

The changes introduce significant performance improvements through memoization and atomic batch operations, with appropriate security hardening. However, there are minor performance concerns in edge cases that should be addressed before merge.

**Key Improvements**:
- 🚀 O(2^n) → O(V+E) complexity reduction for diamond graphs (exponential to linear)
- 🚀 N loop iterations → 1 atomic transaction for multi-dependency adds
- 🔒 Security limits prevent DoS attacks (100 deps/task, 100 chain depth)

**Concerns**:
- ⚠️ Potential O(N) loop for depth validation in batch operations
- ⚠️ Graph cache invalidation happens after every dependency addition
- ℹ️ Pre-existing: Full table scan in findAll() for graph construction

---

## 🔴 Performance Issues in Your Changes (BLOCKING if Severe)

### MEDIUM - Quadratic Complexity in Batch Depth Validation

**File**: `src/implementations/dependency-repository.ts:226-256`
**Severity**: MEDIUM
**Lines ADDED**: 226-256 (new code in addDependencies method)

**Problem**: Loop through all dependencies (up to 100) calling `getMaxDepth()` for each dependency. In worst case, this becomes O(N * (V+E)) where N = number of dependencies being added.

**Code**:
```typescript
// VALIDATION: Check each proposed dependency for cycles
for (const depId of dependsOn) {
  const cycleCheck = graph.wouldCreateCycle(taskId, depId);
  
  if (!cycleCheck.ok) {
    throw cycleCheck.error;
  }
  
  if (cycleCheck.value) {
    throw new DelegateError(
      ErrorCode.INVALID_OPERATION,
      `Cannot add dependency: would create cycle (${taskId} -> ${depId})`
    );
  }
  
  // SECURITY: Check dependency chain depth to prevent stack overflow
  // Calculate depth of the dependency we're adding to
  const depthCheck = graph.getMaxDepth(depId);  // ← Called in loop
  if (!depthCheck.ok) {
    throw depthCheck.error;
  }
  
  const resultingDepth = 1 + depthCheck.value;
  if (resultingDepth > 100) {
    throw new DelegateError(
      ErrorCode.INVALID_OPERATION,
      `Cannot add dependency: would create chain depth of ${resultingDepth} (maximum 100)`
    );
  }
}
```

**Impact**: 
- For adding 100 dependencies (max allowed), calls `getMaxDepth()` 100 times
- Each `getMaxDepth()` call is O(V+E) with memoization
- HOWEVER: `getMaxDepth()` creates NEW memo Map for each call (line 377 in dependency-graph.ts)
- This means memoization is NOT shared across the loop iterations
- Worst case: O(100 * (V+E)) = ~100x slower than necessary

**Fix**: Create memo Map once and pass to `getMaxDepth()`, OR call `getMaxDepth()` once for taskId after adding edges to temp graph:

```typescript
// OPTIMIZATION: Calculate max depth once for the task after adding all proposed edges
// Build temp graph with all proposed edges
const tempGraph = new DependencyGraph([...graph.getAllDependencies(), 
  ...dependsOn.map(depId => ({
    id: -1, 
    taskId, 
    dependsOnTaskId: depId, 
    createdAt: Date.now(),
    resolvedAt: null,
    resolution: 'pending' as const
  }))
]);

// Single depth check for task with all new dependencies
const depthCheck = tempGraph.getMaxDepth(taskId);
if (!depthCheck.ok) {
  throw depthCheck.error;
}

if (depthCheck.value > 100) {
  throw new DelegateError(
    ErrorCode.INVALID_OPERATION,
    `Cannot add dependencies: would create chain depth of ${depthCheck.value} (maximum 100)`
  );
}
```

**Expected improvement**: 100x faster for max batch size (100 deps → 1 depth calculation instead of 100)

**Recommendation**: FIX BEFORE MERGE - This affects the new batch operation feature which is a headline item for v0.3.1

---

### LOW - New Memo Map Created Per getMaxDepth() Call

**File**: `src/core/dependency-graph.ts:375-425`
**Severity**: LOW
**Lines ADDED**: 375-425 (new getMaxDepth method)

**Problem**: Creates new `memo` Map and `visited` Set on every call (line 377-378). If called multiple times on same graph, memoization benefits are lost.

**Code**:
```typescript
getMaxDepth(taskId: TaskId): Result<number> {
  const taskIdStr = taskId as string;
  const memo = new Map<string, number>();  // ← Created fresh each call
  const visited = new Set<string>();       // ← Not used in current implementation
  
  const calculateDepth = (node: string, currentPath: Set<string>): number => {
    // ... uses memo from outer scope
  };
  
  const depth = calculateDepth(taskIdStr, new Set());
  return ok(depth);
}
```

**Impact**: 
- Minimal for single calls
- Compounds the batch validation issue above (each of 100 loop iterations gets new memo)
- `visited` Set is declared but never used (dead code)

**Fix**: 
1. Remove unused `visited` Set (line 378)
2. Consider making memo an optional parameter to allow reuse:

```typescript
getMaxDepth(taskId: TaskId, memo?: Map<string, number>): Result<number> {
  const taskIdStr = taskId as string;
  const memoMap = memo ?? new Map<string, number>();
  
  const calculateDepth = (node: string, currentPath: Set<string>): number => {
    if (currentPath.has(node)) {
      return 0;
    }
    
    if (memoMap.has(node)) {
      return memoMap.get(node)!;
    }
    
    // ... rest of implementation using memoMap
  };
  
  const depth = calculateDepth(taskIdStr, new Set());
  return ok(depth);
}
```

**Expected improvement**: 
- Remove unused variable (minor)
- Enable memo reuse in batch operations (100x improvement when combined with above fix)

**Recommendation**: SHOULD FIX - Low hanging fruit for performance improvement

---

## ⚠️ Issues in Code You Touched (Should Optimize)

### MEDIUM - Graph Cache Invalidated After Every Dependency Add

**File**: `src/implementations/dependency-repository.ts:269`
**Severity**: MEDIUM
**Context**: You modified the cache invalidation logic when refactoring from `addDependency` to `addDependencies`

**Problem**: Cache is invalidated after every batch add, even though the graph is only used for validation BEFORE insertion. This means:
1. First batch add: builds graph from DB (expensive)
2. Cache invalidated after insert
3. Second batch add: builds graph from DB again (expensive)
4. Repeat for every task delegation

**Code**:
```typescript
// All validations passed - insert all dependencies atomically
const createdAt = Date.now();
const createdDependencies: TaskDependency[] = [];

for (const depId of dependsOn) {
  const result = this.addDependencyStmt.run(taskId, depId, createdAt);
  const row = this.getDependencyByIdStmt.get(result.lastInsertRowid) as Record<string, any>;
  createdDependencies.push(this.rowToDependency(row));
}

// PERFORMANCE: Invalidate cache after successful batch insertion
this.cachedGraph = null;  // ← Happens after EVERY add

return createdDependencies;
```

**Impact**:
- For N tasks delegated with dependencies, builds graph from DB N times
- Each `findAll()` is a full table scan: `SELECT * FROM task_dependencies ORDER BY created_at DESC`
- With 1000 tasks, 1000 full table scans instead of 1

**Why This Happens**:
The cache is used for validation, then immediately invalidated. Next operation repeats the cycle.

**Alternative Approach**: 
Update cached graph incrementally instead of invalidating:

```typescript
// PERFORMANCE: Update cache incrementally instead of invalidating
if (this.cachedGraph) {
  for (const dep of createdDependencies) {
    // Add edge to cached graph (DependencyGraph should expose addEdge method)
    this.cachedGraph.addEdge(dep.taskId, dep.dependsOnTaskId);
  }
} else {
  this.cachedGraph = null; // Already null
}
```

**Expected improvement**: 
- 1 full table scan instead of N for N sequential dependency adds
- Major improvement for high-throughput scenarios

**Recommendation**: OPTIMIZE WHILE YOU'RE HERE - Requires adding `addEdge()` method to DependencyGraph class

---

### LOW - Dead Code in getMaxDepth()

**File**: `src/core/dependency-graph.ts:378`
**Severity**: LOW
**Context**: New method you added

**Problem**: `visited` Set is declared but never used

**Code**:
```typescript
getMaxDepth(taskId: TaskId): Result<number> {
  const taskIdStr = taskId as string;
  const memo = new Map<string, number>();
  const visited = new Set<string>();  // ← Declared but never used
  
  const calculateDepth = (node: string, currentPath: Set<string>): number => {
    // Uses currentPath for cycle detection, not visited
    if (currentPath.has(node)) {
      return 0;
    }
    // ...
  };
}
```

**Impact**: Minor - just wastes a Set allocation

**Fix**: Remove line 378

**Expected improvement**: Negligible (tiny memory savings)

**Recommendation**: CLEANUP - Good code hygiene

---

## ℹ️ Pre-existing Performance Issues (Not Blocking)

### HIGH - Full Table Scan for Graph Construction

**File**: `src/implementations/dependency-repository.ts:68-70` (pre-existing)
**Severity**: HIGH
**Context**: Used by code you touched (line 219)

**Problem**: `findAll()` statement performs full table scan without WHERE clause or LIMIT:

**Code**:
```typescript
this.findAllStmt = this.db.prepare(`
  SELECT * FROM task_dependencies ORDER BY created_at DESC
`);
```

**Called from your new code**:
```typescript
// Build dependency graph for cycle detection
let graph: DependencyGraph;
if (this.cachedGraph) {
  graph = this.cachedGraph;
} else {
  const allDepsRows = this.findAllStmt.all() as Record<string, any>[];  // ← Full table scan
  const allDeps = allDepsRows.map(row => this.rowToDependency(row));
  graph = new DependencyGraph(allDeps);
  this.cachedGraph = graph;
}
```

**Impact**:
- Scans entire `task_dependencies` table
- With 10,000 tasks averaging 5 dependencies each = 50,000 rows
- SQLite can handle this, but inefficient
- ORDER BY created_at DESC requires sort (no index on created_at in schema)

**Mitigation**: Cache helps significantly (your code already does this)

**Recommendation for Future PR**:
1. Add index on `created_at` if ordering is important
2. Consider lazy graph construction (only load subgraphs as needed)
3. Consider TTL-based cache instead of invalidation-based

**Why Not Blocking**: Cache significantly reduces impact, only called when cache is cold

---

### MEDIUM - No Index on resolution Column

**File**: Database schema (pre-existing)
**Severity**: MEDIUM
**Context**: Used by isBlocked() query

**Problem**: Query filters by resolution='pending' but no index exists on resolution column:

```sql
SELECT COUNT(*) as count FROM task_dependencies
WHERE task_id = ? AND resolution = 'pending'
```

**Impact**:
- For task with 100 dependencies, scans all 100 rows
- Compound index on (task_id, resolution) would be optimal
- task_id has index via PRIMARY KEY, but resolution doesn't

**Recommendation**: Add compound index in separate PR:
```sql
CREATE INDEX idx_task_dependencies_resolution 
ON task_dependencies(task_id, resolution);
```

**Expected improvement**: Faster isBlocked() checks, especially for tasks with many dependencies

**Why Not Blocking**: 
- Your changes don't introduce this issue
- Impact is moderate (100 rows is small for SQLite)
- Separate optimization PR is appropriate

---

### LOW - N+1 Event Emissions in Batch Operation

**File**: `src/services/handlers/dependency-handler.ts:144-151`
**Severity**: LOW
**Lines MODIFIED**: 144-151 (your changes)

**Problem**: Emits N events sequentially for batch operation instead of single batch event:

**Code**:
```typescript
// Emit success event for each dependency (for compatibility with existing listeners)
if (this.eventBus) {
  for (const dependency of addResult.value) {
    await this.eventBus.emit('TaskDependencyAdded', {
      taskId: dependency.taskId,
      dependsOnTaskId: dependency.dependsOnTaskId
    });
  }
}
```

**Impact**:
- For 100 dependencies, emits 100 events
- Each emit is async, potential event bus overhead
- However, maintains backward compatibility with existing listeners

**Alternative**: Add new `TaskDependenciesAdded` (plural) event:
```typescript
if (this.eventBus) {
  await this.eventBus.emit('TaskDependenciesAdded', {
    taskId: task.id,
    dependsOnTaskIds: addResult.value.map(d => d.dependsOnTaskId),
    dependencies: addResult.value
  });
}
```

**Expected improvement**: 100 event emissions → 1 event emission

**Recommendation**: 
- Optional optimization for future PR
- Requires updating all listeners to handle batch event
- Current approach is safer for backward compatibility

**Why Not Blocking**: 
- Event emission is typically fast
- Maintaining compatibility is valuable
- Can be optimized later without breaking changes

---

## Performance Analysis by Category

### Algorithmic Complexity

✅ **EXCELLENT**: New `getMaxDepth()` algorithm
- Uses DFS with memoization: O(V+E) complexity
- Prevents exponential time on diamond graphs
- Test suite validates performance on complex graph (line 158 test)

⚠️ **CONCERN**: Batch depth validation loop
- O(N * (V+E)) due to repeated getMaxDepth() calls
- Should be O(V+E) with single depth check
- Fixable with optimization mentioned above

### Memory Efficiency

✅ **GOOD**: Memoization prevents redundant computation
- Memo map stores computed depths
- Prevents exponential memory growth

⚠️ **MINOR**: Memo map recreated per call
- Each getMaxDepth() call allocates new Map
- Lost memoization benefits across calls
- Small memory waste (minor issue)

### Database Performance

✅ **EXCELLENT**: Atomic batch operations
- Single transaction for multiple dependencies
- Prevents partial state in database
- TOCTOU protection via synchronous transaction

⚠️ **CONCERN**: Cache invalidation strategy
- Full graph rebuild after every batch add
- Should update cache incrementally
- Causes unnecessary full table scans

ℹ️ **PRE-EXISTING**: Full table scan for graph construction
- No WHERE clause in findAll()
- Mitigated by caching
- Consider indexes for future optimization

### I/O Patterns

✅ **EXCELLENT**: Prepared statements
- All queries use prepared statements
- Prevents SQL injection
- Optimizes query planning

✅ **GOOD**: Single transaction for batch
- All validations + insertions atomic
- Reduces I/O roundtrips

⚠️ **MINOR**: N+1 event emissions
- Sequential event emission for batch
- Low impact (event bus is fast)
- Consider batch event in future

### Caching Strategy

✅ **EXCELLENT**: Graph caching at repository level
- Prevents repeated full table scans
- Correct invalidation (though could be incremental)

✅ **GOOD**: Two-level caching (repo + handler)
- Repository: `cachedGraph`
- Handler: `graphCache`
- Reduces findAll() calls

⚠️ **CONCERN**: Invalidation vs incremental update
- Current: invalidate and rebuild
- Better: update cache incrementally
- Optimization opportunity

---

## Security vs Performance Trade-offs

✅ **WELL BALANCED**: Input validation limits
- Max 100 dependencies per task (prevents DoS)
- Max 100 chain depth (prevents stack overflow)
- Validation has cost but necessary for security

✅ **CORRECT**: Synchronous transactions
- TOCTOU protection more important than async performance
- Better-sqlite3 is fast enough for synchronous operations
- Right trade-off for correctness

⚠️ **OPTIMIZATION NEEDED**: Depth validation in loop
- Security check (depth limit) is good
- Implementation is inefficient (100 calls instead of 1)
- Can maintain security while improving performance

---

## Test Coverage Analysis

✅ **COMPREHENSIVE**: 18 new tests added
- 11 tests for atomic batch operations
- 3 tests for max dependencies validation
- 1 test for max chain depth
- 7 tests for getMaxDepth() algorithm

✅ **PERFORMANCE TEST**: Diamond graph memoization test
```typescript
it('should use memoization for complex diamond graphs (performance)', () => {
  // Complex diamond that would be exponential without memoization
  const startTime = Date.now();
  const result = graph.getMaxDepth(TaskId('A'));
  const endTime = Date.now();
  
  expect(endTime - startTime).toBeLessThan(10); // Should be near-instant
});
```

**Recommendation**: Add test for batch depth validation performance:
```typescript
it('should efficiently validate depth for large batch', () => {
  // Create 100 dependencies for single task
  const startTime = Date.now();
  const result = await repo.addDependencies(taskA.id, [...100 deps]);
  const endTime = Date.now();
  
  expect(endTime - startTime).toBeLessThan(100); // Should be fast even with 100 deps
});
```

---

## Recommendations Summary

### Fix Before Merge (BLOCKING)

1. **Optimize batch depth validation** (dependency-repository.ts:226-256)
   - Change from O(N * (V+E)) to O(V+E)
   - Calculate depth once for task instead of once per dependency
   - Priority: HIGH - Affects new feature performance

### Optimize While You're Here (SHOULD FIX)

1. **Incremental cache updates** (dependency-repository.ts:269)
   - Update cached graph instead of invalidating
   - Requires adding `addEdge()` method to DependencyGraph
   - Priority: MEDIUM - Significant improvement for high throughput

2. **Remove dead code** (dependency-graph.ts:378)
   - Delete unused `visited` Set
   - Priority: LOW - Code hygiene

3. **Add memo parameter to getMaxDepth()** (dependency-graph.ts:375-425)
   - Allow memo reuse across calls
   - Priority: MEDIUM - Enables batch optimization

### Future Work (Optional)

1. **Add database indexes**
   - Index on (task_id, resolution) for isBlocked()
   - Index on created_at for findAll() ordering
   - Priority: MEDIUM - Separate PR

2. **Batch event emission**
   - Add `TaskDependenciesAdded` event
   - Update listeners to handle batch
   - Priority: LOW - Backward compatibility concern

3. **Lazy graph construction**
   - Load subgraphs instead of full graph
   - Complex change, measure first
   - Priority: LOW - Premature optimization

---

## Performance Benchmarks (Estimated)

### Current Implementation

**Scenario**: Add 100 dependencies in batch
- Graph construction: ~5ms (cached: 0ms)
- Cycle checks: 100 * ~1ms = ~100ms
- Depth checks: 100 * ~2ms = ~200ms (NEW BOTTLENECK)
- Database insert: ~10ms (atomic transaction)
- Event emission: 100 * ~0.1ms = ~10ms
- **Total**: ~325ms (cold cache) or ~320ms (warm cache)

### After Optimization

**Scenario**: Add 100 dependencies in batch (with fixes)
- Graph construction: ~5ms (cached: 0ms)
- Cycle checks: 100 * ~1ms = ~100ms
- Depth check: 1 * ~2ms = ~2ms (OPTIMIZED: 100x improvement)
- Database insert: ~10ms (atomic transaction)
- Event emission: 100 * ~0.1ms = ~10ms
- **Total**: ~127ms (cold cache) or ~122ms (warm cache)

**Expected Speedup**: 2.5x faster for max batch size

---

## Conclusion

This is a solid performance-focused release with good algorithmic improvements. The memoization in `getMaxDepth()` is excellent design. However, the batch depth validation loop undermines the performance gains by calling `getMaxDepth()` 100 times instead of once.

**Action Items**:
1. Fix batch depth validation (BLOCKING)
2. Remove dead `visited` variable (SHOULD FIX)
3. Consider incremental cache updates (SHOULD FIX)

With these fixes, the v0.3.1 release will deliver on its performance improvement promises.

---

**Generated**: 2025-11-17 20:20:00
**Auditor**: Claude Code Performance Audit Specialist
**Tool Version**: claude-sonnet-4-5-20250929
