Agent Benchmark Suite

// Advanced benchmarking systemclass 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;  }}

// Advanced regression detection systemclass 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: analysis,      cusum_statistics: cusum.statistics,      sensitivity: sensitivity    };  }    // Machine learning-based regression detection  async detectMLRegression(metrics, historicalData) {    // Train anomaly detection model on historical data    const model = await this.trainAnomalyModel(historicalData);        // Predict anomaly scores for current metrics    const anomalyScores = await model.predict(metrics);        // Identify regressions based on anomaly scores    const threshold = this.calculateDynamicThreshold(anomalyScores);    const regressions = anomalyScores.filter(score => score.anomaly > threshold);        return {      regression_detected: regressions.length > 0,      anomaly_scores: anomalyScores,      threshold: threshold,      regressions: regressions,      model_confidence: model.confidence    };  }}

// Comprehensive automated performance testingclass AutomatedPerformanceTester {  constructor() {    this.testSuites = {      load: new LoadTestSuite(),      stress: new StressTestSuite(),      volume: new VolumeTestSuite(),      endurance: new EnduranceTestSuite(),      spike: new SpikeTestSuite(),      configuration: new ConfigurationTestSuite()    };        this.scheduler = new TestScheduler();    this.orchestrator = new TestOrchestrator();    this.validator = new ResultValidator();  }    // Execute automated performance test campaign  async runTestCampaign(config) {    const campaign = {      id: this.generateCampaignId(),      config,      startTime: Date.now(),      tests: [],      results: new Map(),      summary: null    };        // Schedule test execution    const schedule = await this.scheduler.schedule(config.tests, config.constraints);        // Execute tests according to schedule    for (const scheduledTest of schedule) {      const testResult = await this.executeScheduledTest(scheduledTest);      campaign.tests.push(scheduledTest);      campaign.results.set(scheduledTest.id, testResult);            // Validate results in real-time      const validation = await this.validator.validate(testResult);      if (!validation.valid) {        campaign.summary = {          status: 'failed',          reason: validation.reason,          failedAt: scheduledTest.name        };        break;      }    }        // Generate campaign summary    if (!campaign.summary) {      campaign.summary = await this.generateCampaignSummary(campaign);    }        campaign.endTime = Date.now();    campaign.duration = campaign.endTime - campaign.startTime;        return campaign;  }    // Load testing with gradual ramp-up  async executeLoadTest(config) {    const loadTest = {      type: 'load',      config,      phases: [],      metrics: new Map(),      results: {}    };        // Ramp-up phase    const rampUpResult = await this.executeRampUp(config.rampUp);    loadTest.phases.push({ phase: 'ramp-up', result: rampUpResult });        // Sustained load phase    const sustainedResult = await this.executeSustainedLoad(config.sustained);    loadTest.phases.push({ phase: 'sustained', result: sustainedResult });        // Ramp-down phase    const rampDownResult = await this.executeRampDown(config.rampDown);    loadTest.phases.push({ phase: 'ramp-down', result: rampDownResult });        // Analyze results    loadTest.results = await this.analyzeLoadTestResults(loadTest.phases);        return loadTest;  }    // Stress testing to find breaking points  async executeStressTest(config) {    const stressTest = {      type: 'stress',      config,      breakingPoint: null,      degradationCurve: [],      results: {}    };        let currentLoad = config.startLoad;    let systemBroken = false;        while (!systemBroken && currentLoad <= config.maxLoad) {      const testResult = await this.applyLoad(currentLoad, config.duration);            stressTest.degradationCurve.push({        load: currentLoad,        performance: testResult.performance,        stability: testResult.stability,        errors: testResult.errors      });            // Check if system is breaking      if (this.isSystemBreaking(testResult, config.breakingCriteria)) {        stressTest.breakingPoint = {          load: currentLoad,          performance: testResult.performance,          reason: this.identifyBreakingReason(testResult)        };        systemBroken = true;      }            currentLoad += config.loadIncrement;    }        stressTest.results = await this.analyzeStressTestResults(stressTest);        return stressTest;  }}

// Comprehensive performance validationclass PerformanceValidator {  constructor() {    this.validators = {      sla: new SLAValidator(),      regression: new RegressionValidator(),      scalability: new ScalabilityValidator(),      reliability: new ReliabilityValidator(),      efficiency: new EfficiencyValidator()    };        this.thresholds = new ThresholdManager();    this.rules = new ValidationRuleEngine();  }    // Validate performance against defined criteria  async validatePerformance(results, criteria) {    const validation = {      overall: {        passed: true,        score: 0,        violations: []      },      detailed: new Map(),      recommendations: []    };        // Run all validators    const validationPromises = Object.entries(this.validators).map(      async ([type, validator]) => {        const result = await validator.validate(results, criteria[type]);        return [type, result];      }    );        const validationResults = await Promise.all(validationPromises);        // Aggregate validation results    for (const [type, result] of validationResults) {      validation.detailed.set(type, result);            if (!result.passed) {        validation.overall.passed = false;        validation.overall.violations.push(...result.violations);      }            validation.overall.score += result.score * (criteria[type]?.weight || 1);    }        // Normalize overall score    const totalWeight = Object.values(criteria).reduce((sum, c) => sum + (c.weight || 1), 0);    validation.overall.score /= totalWeight;        // Generate recommendations    validation.recommendations = await this.generateValidationRecommendations(validation);        return validation;  }    // SLA validation  async validateSLA(results, slaConfig) {    const slaValidation = {      passed: true,      violations: [],      score: 1.0,      metrics: {}    };        // Validate each SLA metric    for (const [metric, threshold] of Object.entries(slaConfig.thresholds)) {      const actualValue = this.extractMetricValue(results, metric);      const validation = this.validateThreshold(actualValue, threshold);            slaValidation.metrics[metric] = {        actual: actualValue,        threshold: threshold.value,        operator: threshold.operator,        passed: validation.passed,        deviation: validation.deviation      };            if (!validation.passed) {        slaValidation.passed = false;        slaValidation.violations.push({          metric,          actual: actualValue,          expected: threshold.value,          severity: threshold.severity || 'medium'        });                // Reduce score based on violation severity        const severityMultiplier = this.getSeverityMultiplier(threshold.severity);        slaValidation.score -= (validation.deviation * severityMultiplier);      }    }        slaValidation.score = Math.max(0, slaValidation.score);        return slaValidation;  }    // Scalability validation  async validateScalability(results, scalabilityConfig) {    const scalabilityValidation = {      passed: true,      violations: [],      score: 1.0,      analysis: {}    };        // Linear scalability analysis    if (scalabilityConfig.linear) {      const linearityAnalysis = this.analyzeLinearScalability(results);      scalabilityValidation.analysis.linearity = linearityAnalysis;            if (linearityAnalysis.coefficient < scalabilityConfig.linear.minCoefficient) {        scalabilityValidation.passed = false;        scalabilityValidation.violations.push({          type: 'linearity',          actual: linearityAnalysis.coefficient,          expected: scalabilityConfig.linear.minCoefficient        });      }    }        // Efficiency retention analysis    if (scalabilityConfig.efficiency) {      const efficiencyAnalysis = this.analyzeEfficiencyRetention(results);      scalabilityValidation.analysis.efficiency = efficiencyAnalysis;            if (efficiencyAnalysis.retention < scalabilityConfig.efficiency.minRetention) {        scalabilityValidation.passed = false;        scalabilityValidation.violations.push({          type: 'efficiency_retention',          actual: efficiencyAnalysis.retention,          expected: scalabilityConfig.efficiency.minRetention        });      }    }        return scalabilityValidation;  }}

// Comprehensive MCP benchmark integrationconst benchmarkIntegration = {  // Execute performance benchmarks  async runBenchmarks(config = {}) {    // Run benchmark suite    const benchmarkResult = await mcp.benchmark_run({      suite: config.suite || 'comprehensive'    });        // Collect detailed metrics during benchmarking    const metrics = await mcp.metrics_collect({      components: ['system', 'agents', 'coordination', 'memory']    });        // Analyze performance trends    const trends = await mcp.trend_analysis({      metric: 'performance',      period: '24h'    });        // Cost analysis    const costAnalysis = await mcp.cost_analysis({      timeframe: '24h'    });        return {      benchmark: benchmarkResult,      metrics,      trends,      costAnalysis,      timestamp: Date.now()    };  },    // Quality assessment  async assessQuality(criteria) {    const qualityAssessment = await mcp.quality_assess({      target: 'swarm-performance',      criteria: criteria || [        'throughput',        'latency',        'reliability',        'scalability',        'efficiency'      ]    });        return qualityAssessment;  },    // Error pattern analysis  async analyzeErrorPatterns() {    // Collect system logs    const logs = await this.collectSystemLogs();        // Analyze error patterns    const errorAnalysis = await mcp.error_analysis({      logs: logs    });        return errorAnalysis;  }};

// Comprehensive benchmark definitionsconst standardBenchmarks = {  // Throughput benchmarks  throughput: {    name: 'Throughput Benchmark',    metrics: ['requests_per_second', 'tasks_per_second', 'messages_per_second'],    duration: 300000, // 5 minutes    warmup: 30000,    // 30 seconds    targets: {      requests_per_second: { min: 1000, optimal: 5000 },      tasks_per_second: { min: 100, optimal: 500 },      messages_per_second: { min: 10000, optimal: 50000 }    }  },    // Latency benchmarks  latency: {    name: 'Latency Benchmark',    metrics: ['p50', 'p90', 'p95', 'p99', 'max'],    duration: 300000,    targets: {      p50: { max: 100 },   // 100ms      p90: { max: 200 },   // 200ms      p95: { max: 500 },   // 500ms      p99: { max: 1000 },  // 1s      max: { max: 5000 }   // 5s    }  },    // Scalability benchmarks  scalability: {    name: 'Scalability Benchmark',    metrics: ['linear_coefficient', 'efficiency_retention'],    load_points: [1, 2, 4, 8, 16, 32, 64],    targets: {      linear_coefficient: { min: 0.8 },      efficiency_retention: { min: 0.7 }    }  }};