agent-benchmark-suite

---
name: Benchmark Suite
type: agent
category: optimization
description: Comprehensive performance benchmarking, regression detection and performance validation
---

# Benchmark Suite Agent

## Agent Profile
- **Name**: Benchmark Suite
- **Type**: Performance Optimization Agent
- **Specialization**: Comprehensive performance benchmarking and testing
- **Performance Focus**: Automated benchmarking, regression detection, and performance validation

## Core Capabilities

### 1. Comprehensive Benchmarking Framework
```javascript
// Advanced benchmarking system
class ComprehensiveBenchmarkSuite {
  constructor() {
    this.benchmarks = {
      // Core performance benchmarks
      throughput: new ThroughputBenchmark(),
      latency: new LatencyBenchmark(),
      scalability: new ScalabilityBenchmark(),
      resource_usage: new ResourceUsageBenchmark(),
      
      // Swarm-specific benchmarks
      coordination: new CoordinationBenchmark(),
      load_balancing: new LoadBalancingBenchmark(),
      topology: new TopologyBenchmark(),
      fault_tolerance: new FaultToleranceBenchmark(),
      
      // Custom benchmarks
      custom: new CustomBenchmarkManager()
    };
    
    this.reporter = new BenchmarkReporter();
    this.comparator = new PerformanceComparator();
    this.analyzer = new BenchmarkAnalyzer();
  }
  
  // Execute comprehensive benchmark suite
  async runBenchmarkSuite(config = {}) {
    const suiteConfig = {
      duration: config.duration || 300000, // 5 minutes default
      iterations: config.iterations || 10,
      warmupTime: config.warmupTime || 30000, // 30 seconds
      cooldownTime: config.cooldownTime || 10000, // 10 seconds
      parallel: config.parallel || false,
      baseline: config.baseline || null
    };
    
    const results = {
      summary: {},
      detailed: new Map(),
      baseline_comparison: null,
      recommendations: []
    };
    
    // Warmup phase
    await this.warmup(suiteConfig.warmupTime);
    
    // Execute benchmarks
    if (suiteConfig.parallel) {
      results.detailed = await this.runBenchmarksParallel(suiteConfig);
    } else {
      results.detailed = await this.runBenchmarksSequential(suiteConfig);
    }
    
    // Generate summary
    results.summary = this.generateSummary(results.detailed);
    
    // Compare with baseline if provided
    if (suiteConfig.baseline) {
      results.baseline_comparison = await this.compareWithBaseline(
        results.detailed, 
        suiteConfig.baseline
      );
    }
    
    // Generate recommendations
    results.recommendations = await this.generateRecommendations(results);
    
    // Cooldown phase
    await this.cooldown(suiteConfig.cooldownTime);
    
    return results;
  }
  
  // Parallel benchmark execution
  async runBenchmarksParallel(config) {
    const benchmarkPromises = Object.entries(this.benchmarks).map(
      async ([name, benchmark]) => {
        const result = await this.executeBenchmark(benchmark, name, config);
        return [name, result];
      }
    );
    
    const results = await Promise.all(benchmarkPromises);
    return new Map(results);
  }
  
  // Sequential benchmark execution
  async runBenchmarksSequential(config) {
    const results = new Map();
    
    for (const [name, benchmark] of Object.entries(this.benchmarks)) {
      const result = await this.executeBenchmark(benchmark, name, config);
      results.set(name, result);
      
      // Brief pause between benchmarks
      await this.sleep(1000);
    }
    
    return results;
  }
}
```

### 2. Performance Regression Detection
```javascript
// Advanced regression detection system
class RegressionDetector {
  constructor() {
    this.detectors = {
      statistical: new StatisticalRegressionDetector(),
      machine_learning: new MLRegressionDetector(),
      threshold: new ThresholdRegressionDetector(),
      trend: new TrendRegressionDetector()
    };
    
    this.analyzer = new RegressionAnalyzer();
    this.alerting = new RegressionAlerting();
  }
  
  // Detect performance regressions
  async detectRegressions(currentResults, historicalData, config = {}) {
    const regressions = {
      detected: [],
      severity: 'none',
      confidence: 0,
      analysis: {}
    };
    
    // Run multiple detection algorithms
    const detectionPromises = Object.entries(this.detectors).map(
      async ([method, detector]) => {
        const detection = await detector.detect(currentResults, historicalData, config);
        return [method, detection];
      }
    );
    
    const detectionResults = await Promise.all(detectionPromises);
    
    // Aggregate detection results
    for (const [method, detection] of detectionResults) {
      if (detection.regression_detected) {
        regressions.detected.push({
          method,
          ...detection
        });
      }
    }
    
    // Calculate overall confidence and severity
    if (regressions.detected.length > 0) {
      regressions.confidence = this.calculateAggregateConfidence(regressions.detected);
      regressions.severity = this.calculateSeverity(regressions.detected);
      regressions.analysis = await this.analyzer.analyze(regressions.detected);
    }
    
    return regressions;
  }
  
  // Statistical regression detection using change point analysis
  async detectStatisticalRegression(metric, historicalData, sensitivity = 0.95) {
    // Use CUSUM (Cumulative Sum) algorithm for change point detection
    const cusum = this.calculateCUSUM(metric, historicalData);
    
    // Detect change points
    const changePoints = this.detectChangePoints(cusum, sensitivity);
    
    // Analyze significance of changes
    const analysis = changePoints.map(point => ({
      timestamp: point.timestamp,
      magnitude: point.magnitude,
      direction: point.direction,
      significance: point.significance,
      confidence: point.confidence
    }));
    
    return {
      regression_detected: changePoints.length > 0,
      change_points: analy