benchmark-suite
Comprehensive performance benchmarking, regression detection and performance validation
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Comprehensive performance benchmarking, regression detection and performance validation
Agent definition
benchmark-suite.mdname: 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
// 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
// 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: analysRead more
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
// 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
// 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: analysAI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.
Repo: spencermarx/open-code-review
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