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* @license
* Copyright 2026 Google LLC
* SPDX-License-Identifier: Apache-2.0
*/
import { performance } from 'node:perf_hooks';
import { setTimeout as sleep } from 'node:timers/promises';
import { readFileSync, writeFileSync, existsSync } from 'node:fs';
/** Configuration for asciichart plot function. */
interface PlotConfig {
height?: number;
format?: (x: number) => string;
}
/** Type for the asciichart plot function. */
type PlotFn = (series: number[], config?: PlotConfig) => string;
/**
* Baseline entry for a single performance test scenario.
*/
export interface PerfBaseline {
wallClockMs: number;
cpuTotalUs: number;
timestamp: string;
}
/**
* Top-level structure of the perf baselines JSON file.
*/
export interface PerfBaselineFile {
version: number;
updatedAt: string;
scenarios: Record<string, PerfBaseline>;
}
/**
* A single performance snapshot at a point in time.
*/
export interface PerfSnapshot {
timestamp: number;
label: string;
wallClockMs: number;
cpuUserUs: number;
cpuSystemUs: number;
cpuTotalUs: number;
eventLoopDelayP50Ms: number;
eventLoopDelayP95Ms: number;
eventLoopDelayMaxMs: number;
childEventLoopDelayP50Ms?: number;
childEventLoopDelayP95Ms?: number;
childEventLoopDelayMaxMs?: number;
}
/**
* Result from running a performance test scenario.
*/
export interface PerfTestResult {
scenarioName: string;
samples: PerfSnapshot[];
filteredSamples: PerfSnapshot[];
median: PerfSnapshot;
baseline: PerfBaseline | undefined;
withinTolerance: boolean;
deltaPercent: number;
cpuDeltaPercent: number;
}
/**
* Options for the PerfTestHarness.
*/
export interface PerfTestHarnessOptions {
/** Path to the baselines JSON file */
baselinesPath: string;
/** Default tolerance percentage (0-100). Default: 15 */
defaultTolerancePercent?: number;
/** Default CPU tolerance percentage (0-100). Optional */
defaultCpuTolerancePercent?: number;
/** Number of samples per scenario. Default: 5 */
sampleCount?: number;
/** Number of warmup runs to discard. Default: 1 */
warmupCount?: number;
/** Pause in ms between samples. Default: 100 */
samplePauseMs?: number;
}
/**
* Active timer state tracked internally.
*/
interface ActiveTimer {
label: string;
startTime: number;
startCpuUsage: NodeJS.CpuUsage;
}
/**
* PerfTestHarness provides infrastructure for running CPU performance tests.
*
* It handles:
* - High-resolution wall-clock timing via performance.now()
* - CPU usage measurement via process.cpuUsage()
* - Event loop delay monitoring via perf_hooks.monitorEventLoopDelay()
* - IQR outlier filtering for noise reduction
* - Warmup runs to avoid JIT compilation noise
* - Comparing against baselines with configurable tolerance
* - Generating ASCII chart reports
*/
export class PerfTestHarness {
private baselines: PerfBaselineFile;
private readonly baselinesPath: string;
private readonly defaultTolerancePercent: number;
private readonly defaultCpuTolerancePercent?: number;
private readonly sampleCount: number;
private readonly warmupCount: number;
private readonly samplePauseMs: number;
private allResults: PerfTestResult[] = [];
private activeTimers: Map<string, ActiveTimer> = new Map();
constructor(options: PerfTestHarnessOptions) {
this.baselinesPath = options.baselinesPath;
this.defaultTolerancePercent = options.defaultTolerancePercent ?? 15;
this.defaultCpuTolerancePercent = options.defaultCpuTolerancePercent;
this.sampleCount = options.sampleCount ?? 5;
this.warmupCount = options.warmupCount ?? 1;
this.samplePauseMs = options.samplePauseMs ?? 100;
this.baselines = loadPerfBaselines(this.baselinesPath);
}
/**
* Start a high-resolution timer with CPU tracking.
*/
startTimer(label: string): void {
this.activeTimers.set(label, {
label,
startTime: performance.now(),
startCpuUsage: process.cpuUsage(),
});
}
/**
* Stop a timer and return the snapshot.
*/
stopTimer(label: string): PerfSnapshot {
const timer = this.activeTimers.get(label);
if (!timer) {
throw new Error(`No active timer found for label "${label}"`);
}
// Round wall-clock time to nearest 0.1 ms
const wallClockMs =
Math.round((performance.now() - timer.startTime) * 10) / 10;
const cpuDelta = process.cpuUsage(timer.startCpuUsage);
this.activeTimers.delete(label);
return {
timestamp: Date.now(),
label,
wallClockMs,
cpuUserUs: cpuDelta.user,
cpuSystemUs: cpuDelta.system,
cpuTotalUs: cpuDelta.user + cpuDelta.system,
eventLoopDelayP50Ms: 0,
eventLoopDelayP95Ms: 0,
eventLoopDelayMaxMs: 0,
};
}
/**
* Measure a function's wall-clock time and CPU usage.
* Returns the snapshot with timing data.
*/
async measure(label: string, fn: () => Promise<void>): Promise<PerfSnapshot> {
this.startTimer(label);
await fn();
return this.stopTimer(label);
}
/**
* Measure a function with event loop delay monitoring.
* Uses perf_hooks.monitorEventLoopDelay() for histogram data.
*/
async measureWithEventLoop(
label: string,
fn: () => Promise<void>,
): Promise<PerfSnapshot> {
// monitorEventLoopDelay is available in Node.js 12+
const { monitorEventLoopDelay } = await import('node:perf_hooks');
const histogram = monitorEventLoopDelay({ resolution: 10 });
histogram.enable();
this.startTimer(label);
await fn();
const snapshot = this.stopTimer(label);
histogram.disable();
// Convert from nanoseconds to milliseconds
snapshot.eventLoopDelayP50Ms = histogram.percentile(50) / 1e6;
snapshot.eventLoopDelayP95Ms = histogram.percentile(95) / 1e6;
snapshot.eventLoopDelayMaxMs = histogram.max / 1e6;
return snapshot;
}
/**
* Run a scenario multiple times with warmup, outlier filtering, and baseline comparison.
*
* @param name - Scenario name (must match baseline key)
* @param fn - Async function that executes one sample of the scenario.
* Must return a PerfSnapshot with measured values.
* @param tolerancePercent - Override default tolerance for this scenario
*/
async runScenario(
name: string,
fn: () => Promise<PerfSnapshot>,
tolerancePercent?: number,
): Promise<PerfTestResult> {
const tolerance = tolerancePercent ?? this.defaultTolerancePercent;
const totalRuns = this.warmupCount + this.sampleCount;
const allSnapshots: PerfSnapshot[] = [];
for (let i = 0; i < totalRuns; i++) {
const isWarmup = i < this.warmupCount;
const snapshot = await fn();
snapshot.label = isWarmup
? `warmup-${i}`
: `sample-${i - this.warmupCount}`;
if (!isWarmup) {
allSnapshots.push(snapshot);
}
// Brief pause between samples
await sleep(this.samplePauseMs);
}
// Apply IQR outlier filtering on wall-clock time
const filteredSnapshots = this.filterOutliers(allSnapshots, 'wallClockMs');
// Get median of filtered samples
const median = this.getMedianSnapshot(filteredSnapshots);
median.label = 'median';
// Get baseline
const baseline = this.baselines.scenarios[name];
// Determine if within tolerance
let deltaPercent = 0;
let cpuDeltaPercent = 0;
let withinTolerance = true;
if (baseline) {
deltaPercent =
((median.wallClockMs - baseline.wallClockMs) / baseline.wallClockMs) *
100;
cpuDeltaPercent =
((median.cpuTotalUs - baseline.cpuTotalUs) / baseline.cpuTotalUs) * 100;
withinTolerance = deltaPercent <= tolerance;
}
const result: PerfTestResult = {
scenarioName: name,
samples: allSnapshots,
filteredSamples: filteredSnapshots,
median,
baseline,
withinTolerance,
deltaPercent,
cpuDeltaPercent,
};
this.allResults.push(result);
return result;
}
/**
* Assert that a scenario result is within the baseline tolerance.
*/
assertWithinBaseline(
result: PerfTestResult,
tolerancePercent?: number,
cpuTolerancePercent?: number,
): void {
const tolerance = tolerancePercent ?? this.defaultTolerancePercent;
const cpuTolerance = cpuTolerancePercent ?? this.defaultCpuTolerancePercent;
if (!result.baseline) {
console.warn(
`β No baseline found for "${result.scenarioName}". ` +
`Run with UPDATE_PERF_BASELINES=true to create one. ` +
`Measured: ${result.median.wallClockMs.toFixed(1)} ms wall-clock.`,
);
return;
}
const deltaPercent =
((result.median.wallClockMs - result.baseline.wallClockMs) /
result.baseline.wallClockMs) *
100;
if (deltaPercent > tolerance) {
throw new Error(
`Performance regression detected for "${result.scenarioName}"!\n` +
` Measured: ${result.median.wallClockMs.toFixed(1)} ms wall-clock\n` +
` Baseline: ${result.baseline.wallClockMs.toFixed(1)} ms wall-clock\n` +
` Delta: ${deltaPercent.toFixed(1)}% (tolerance: ${tolerance}%)\n` +
` CPU total: ${formatUs(result.median.cpuTotalUs)}\n` +
` Samples: ${result.samples.length} (${result.filteredSamples.length} after IQR filter)`,
);
}
if (cpuTolerance !== undefined && result.cpuDeltaPercent > cpuTolerance) {
throw new Error(
`CPU usage regression detected for "${result.scenarioName}"!\n` +
` Measured: ${formatUs(result.median.cpuTotalUs)}\n` +
` Baseline: ${formatUs(result.baseline.cpuTotalUs)}\n` +
` Delta: ${result.cpuDeltaPercent.toFixed(1)}% (tolerance: ${cpuTolerance}%)\n` +
` Wall-clock: ${result.median.wallClockMs.toFixed(1)} ms`,
);
}
}
/**
* Update the baseline for a scenario with the current measured values.
*/
updateScenarioBaseline(result: PerfTestResult): void {
updatePerfBaseline(this.baselinesPath, result.scenarioName, {
wallClockMs: result.median.wallClockMs,
cpuTotalUs: result.median.cpuTotalUs,
});
// Reload baselines after update
this.baselines = loadPerfBaselines(this.baselinesPath);
console.log(
`Updated baseline for ${result.scenarioName}: ${result.median.wallClockMs.toFixed(1)} ms`,
);
}
/**
* Generate an ASCII report with summary table and charts.
*/
async generateReport(results?: PerfTestResult[]): Promise<string> {
const resultsToReport = results ?? this.allResults;
const lines: string[] = [];
lines.push('');
lines.push('βββββββββββββββββββββββββββββββββββββββββββββββββββ');
lines.push(' PERFORMANCE TEST REPORT');
lines.push('βββββββββββββββββββββββββββββββββββββββββββββββββββ');
lines.push('');
for (const result of resultsToReport) {
const measured = `${result.median.wallClockMs.toFixed(1)} ms`;
const baseline = result.baseline
? `${result.baseline.wallClockMs.toFixed(1)} ms`
: 'N/A';
const delta = result.baseline
? `${result.deltaPercent >= 0 ? '+' : ''}${result.deltaPercent.toFixed(1)}%`
: 'N/A';
const status = !result.baseline
? 'NEW'
: result.withinTolerance
? 'β
'
: 'β';
lines.push(
`${result.scenarioName}: ${measured} (Baseline: ${baseline}, Delta: ${delta}) ${status}`,
);
// Show CPU breakdown
const cpuMs = `${(result.median.cpuTotalUs / 1000).toFixed(1)} ms`;
lines.push(
` CPU: ${cpuMs} (user: ${formatUs(result.median.cpuUserUs)}, system: ${formatUs(result.median.cpuSystemUs)})`,
);
if (result.median.eventLoopDelayMaxMs > 0) {
lines.push(
` Event loop (runner): p50=${result.median.eventLoopDelayP50Ms.toFixed(1)}ms p95=${result.median.eventLoopDelayP95Ms.toFixed(1)}ms max=${result.median.eventLoopDelayMaxMs.toFixed(1)}ms`,
);
}
if (
result.median.childEventLoopDelayMaxMs !== undefined &&
result.median.childEventLoopDelayMaxMs > 0
) {
lines.push(
` Event loop (CLI): p50=${result.median.childEventLoopDelayP50Ms!.toFixed(1)}ms p95=${result.median.childEventLoopDelayP95Ms!.toFixed(1)}ms max=${result.median.childEventLoopDelayMaxMs!.toFixed(1)}ms`,
);
}
lines.push(
` Samples: ${result.samples.length} β ${result.filteredSamples.length} after IQR filter`,
);
}
lines.push('');
// Generate ASCII chart for wall-clock per scenario
try {
// @ts-expect-error - asciichart may not have types
const asciichart = (await import('asciichart')) as {
default?: { plot?: PlotFn };
plot?: PlotFn;
};
const plot: PlotFn | undefined =
asciichart.default?.plot ?? asciichart.plot;
for (const result of resultsToReport) {
if (result.filteredSamples.length > 2) {
lines.push(`π Wall-clock trend: ${result.scenarioName}`);
lines.push('β'.repeat(60));
const wallClockData = result.filteredSamples.map(
(s) => s.wallClockMs,
);
if (plot) {
const chart = plot(wallClockData, {
height: 8,
format: (x: number) => `${x.toFixed(0)} ms`.padStart(10),
});
lines.push(chart);
}
const labels = result.filteredSamples.map((s) => s.label);
lines.push(' ' + labels.join(' β '));
lines.push('');
}
}
} catch {
lines.push(
'(asciichart not available β install with: npm install --save-dev asciichart)',
);
lines.push('');
}
lines.push('βββββββββββββββββββββββββββββββββββββββββββββββββββ');
lines.push('');
const report = lines.join('\n');
console.log(report);
return report;
}
/**
* Filter outliers using the Interquartile Range (IQR) method.
* Removes samples where the given metric falls outside Q1 - 1.5*IQR or Q3 + 1.5*IQR.
*/
private filterOutliers(
snapshots: PerfSnapshot[],
metric: keyof PerfSnapshot,
): PerfSnapshot[] {
if (snapshots.length < 4) {
// Not enough data for meaningful IQR filtering
return [...snapshots];
}
const sorted = [...snapshots].sort(
(a, b) => (a[metric] as number) - (b[metric] as number),
);
const q1Idx = Math.floor(sorted.length * 0.25);
const q3Idx = Math.floor(sorted.length * 0.75);
const q1 = sorted[q1Idx]![metric] as number;
const q3 = sorted[q3Idx]![metric] as number;
const iqr = q3 - q1;
const lowerBound = q1 - 1.5 * iqr;
const upperBound = q3 + 1.5 * iqr;
return snapshots.filter((s) => {
const val = s[metric] as number;
return val >= lowerBound && val <= upperBound;
});
}
/**
* Get the median snapshot by wall-clock time from a sorted list.
*/
private getMedianSnapshot(snapshots: PerfSnapshot[]): PerfSnapshot {
if (snapshots.length === 0) {
throw new Error('Cannot compute median of empty snapshot list');
}
const sorted = [...snapshots].sort((a, b) => a.wallClockMs - b.wallClockMs);
const medianIdx = Math.floor(sorted.length / 2);
return { ...sorted[medianIdx]! };
}
}
// βββ Baseline management βββββββββββββββββββββββββββββββββββββββββββββ
/**
* Load perf baselines from a JSON file.
*/
export function loadPerfBaselines(path: string): PerfBaselineFile {
if (!existsSync(path)) {
return {
version: 1,
updatedAt: new Date().toISOString(),
scenarios: {},
};
}
const content = readFileSync(path, 'utf-8');
return JSON.parse(content) as PerfBaselineFile;
}
/**
* Save perf baselines to a JSON file.
*/
export function savePerfBaselines(
path: string,
baselines: PerfBaselineFile,
): void {
baselines.updatedAt = new Date().toISOString();
writeFileSync(path, JSON.stringify(baselines, null, 2) + '\n');
}
/**
* Update (or create) a single scenario baseline in the file.
*/
export function updatePerfBaseline(
path: string,
scenarioName: string,
measured: {
wallClockMs: number;
cpuTotalUs: number;
},
): void {
const baselines = loadPerfBaselines(path);
baselines.scenarios[scenarioName] = {
wallClockMs: measured.wallClockMs,
cpuTotalUs: measured.cpuTotalUs,
timestamp: new Date().toISOString(),
};
savePerfBaselines(path, baselines);
}
// βββ Helpers βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
/**
* Format microseconds as a human-readable string.
*/
function formatUs(us: number): string {
if (us > 1_000_000) {
return `${(us / 1_000_000).toFixed(2)} s`;
}
if (us > 1_000) {
return `${(us / 1_000).toFixed(1)} ms`;
}
return `${us} ΞΌs`;
}
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