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#!/usr/bin/env node
/**
* CI benchmark script for @arbiter/core — powered by @tenere/benchmark-lib
* (possibilistic contours with valid alpha cuts).
*
* node --expose-gc scripts/benchmark.js compare against baseline
* node --expose-gc scripts/benchmark.js --save save new baseline
* node --expose-gc scripts/benchmark.js --json JSON output
* node --expose-gc scripts/benchmark.js --baseline <path> custom baseline path
*
* Exit codes:
* 0 — all benchmarks pass, no high-severity regressions
* 1 — high-severity regression found
* 2 — crash (benchmark threw unexpectedly)
*/
import fs from 'fs'
import { benchmark, createBaseline, detectRegressions, formatRegressions } from '@tenere/benchmark-lib'
import { Arbiter } from '../src/core/Arbiter.js'
import { PartialGraphContext } from '../src/core/PartialGraphContext.js'
const SAVE = process.argv.includes('--save')
const AS_JSON = process.argv.includes('--json')
const BASELINE_PATH = (() => {
const idx = process.argv.indexOf('--baseline')
return idx >= 0 ? process.argv[idx + 1] : '.rigor-baseline.json'
})()
benchmark.config({
measurements: ['timing'],
// Stop collecting once 90% confident (was 0.99 ≈ "confident" immediately,
// so the loop stopped at the first check and the sub-ms checks were
// measured from ~5 noisy samples). A tighter threshold forces the loop to
// keep sampling until variance actually tightens.
uncertaintyThreshold: 0.1,
// Sample-count floor before any early stop (was 0). Sub-ms checks need a
// real sample population for a stable mostPlausible / p95.
minSamples: 200,
// Headroom for noisy actions to run to (was 200, which was the effective
// cap and doubled as the practical floor).
maxSamples: 2000,
overheadCompensation: true,
// Per-sample GC injected a global.gc() between every iteration, which
// dominated sub-ms timings and produced the wild run-to-run swings
// (check[overlay-on-top] flagged -23%..-83% "faster" across runs of
// unchanged code). GC is left to the runtime; the sample floor + tight
// confidence threshold now stabilize the distribution instead.
gcBetweenSamples: false,
})
let CRASHED = 0
// ── Fixtures ──────────────────────────────────────────────────────────
function buildEngine() {
const a = new Arbiter()
const groupCount = 40
for (let g = 0; g < groupCount; g++) a.addNode(`group:${g}`, 'group')
for (let u = 0; u < 200; u++) {
a.addNode(`user:${u}`, 'user')
a.addNode(`doc:${u}`, 'doc')
}
a.setRelationConfig('owner', { type: 'direct' })
a.setRelationConfig('member_of', { type: 'direct' })
a.setRelationConfig('can_read', {
type: 'union',
rules: [{ kind: 'direct', relation: 'owner' }, { kind: 'tuple_to_userset', parentRelation: 'member_of', childRelation: 'owner' }]
})
for (let u = 0; u < 200; u++) {
a.addRelation(`user:${u}`, 'owner', `doc:${u}`, { possibility: 0.9 + (u % 10) / 100 })
a.addRelation(`user:${u}`, 'member_of', `group:${u % groupCount}`, { possibility: 0.7 })
}
for (let g = 0; g < groupCount; g++) a.addRelation(`group:${g}`, 'owner', `doc:${g}`, { possibility: 1.0 })
return a
}
const engine = buildEngine()
// ── Warmup ────────────────────────────────────────────────────────────
// Sub-ms checks measured without a warmup phase mix first-touch allocation,
// lazy index construction, and JIT compilation into the sample population —
// a bimodal distribution (check[direct-hit] ~4µs vs ~20µs) that flapped the
// regression gate across runs of unchanged code. Run each hot path to a
// steady state before any sampling.
function warmupChecks(a, iterations = 20000) {
const ctx = new PartialGraphContext(a, {
relations: [{ src: 'user:1', relation: 'owner', dst: 'doc:1', possibility: 0.5 }]
})
for (let i = 0; i < iterations; i++) {
a.check('user:1', 'owner', 'doc:1')
a.check('user:1', 'can_read', 'doc:1')
a.check('user:5', 'owner', 'doc:1')
a.check('user:1', 'can_read', 'doc:1', { includeMeta: true })
a.check('user:1', 'owner', 'doc:1', { partialGraphContext: ctx })
}
}
warmupChecks(engine)
// Sub-ms checks are 420µs per call — below reliable single-call timing
// resolution, so one GC tick or context switch inflates a sample (bimodal
// distributions flapped the gate). Each sub-ms action measures a BATCH of
// calls per sample; jitter amortizes across the batch and the relative
// comparison against the baseline (which uses the same BATCH) stays exact.
const BATCH = 100
const directBench = benchmark('check[direct-hit]', () => {
for (let i = 0; i < BATCH; i++) engine.check('user:1', 'owner', 'doc:1')
})
const unionBench = benchmark('check[union-ttu]', () => {
for (let i = 0; i < BATCH; i++) engine.check('user:1', 'can_read', 'doc:1')
})
const deniedBench = benchmark('check[denied-miss]', () => {
for (let i = 0; i < BATCH; i++) engine.check('user:5', 'owner', 'doc:1')
})
const metaBench = benchmark('check[include-meta]', () => {
for (let i = 0; i < BATCH; i++) engine.check('user:1', 'can_read', 'doc:1', { includeMeta: true })
})
const overlayBench = benchmark('check[overlay-on-top]', () => {
for (let i = 0; i < BATCH; i++) {
const ctx = new PartialGraphContext(engine, {
relations: [{ src: 'user:1', relation: 'owner', dst: 'doc:1', possibility: 0.5 }]
})
engine.check('user:1', 'owner', 'doc:1', { partialGraphContext: ctx })
}
})
const binaryBench = (() => {
const snap = buildEngine()
snap.enableCondensedSnapshot()
for (let i = 0; i < 5000; i++) snap.check('user:1', 'owner', 'doc:1', { binary: true })
return benchmark('check[binary-direct]', () => {
for (let i = 0; i < BATCH; i++) snap.check('user:1', 'owner', 'doc:1', { binary: true })
})
})()
const snapshotBuildBench = (() => {
const snap = buildEngine()
snap.enableCondensedSnapshot()
return benchmark('snapshot[build-binary]', () => {
snap.toSnapshotBinary()
})
})()
const snapshotRestoreBench = (() => {
const snap = buildEngine()
snap.enableCondensedSnapshot()
const buf = snap.toSnapshotBinary()
return benchmark('snapshot[restore-binary]', () => {
Arbiter.fromSnapshotBinary(buf)
})
})()
// ── Run ───────────────────────────────────────────────────────────────
function measure(handle) {
try {
return handle.contour('timing')
} catch (e) {
CRASHED++
console.error(`${e.message}`)
return null
}
}
const results = {}
const order = [directBench, unionBench, deniedBench, metaBench, overlayBench, binaryBench, snapshotBuildBench, snapshotRestoreBench]
for (const handle of order) {
const contour = measure(handle)
if (!contour) continue
const mp = contour.mostPlausible()
results[handle.name] = {
mostPlausible: mp.value,
alphaCuts: contour.alphaCuts(),
}
}
const current = { actions: results, campaign: null, failures: 0 }
if (AS_JSON) {
const out = { results: {}, regressions: [], improvements: [], crashed: CRASHED }
for (const [name, r] of Object.entries(results)) {
out.results[name] = { timing: { mp: r.mostPlausible, alphaCuts: r.alphaCuts } }
}
if (fs.existsSync(BASELINE_PATH) && !SAVE) {
const baseline = JSON.parse(fs.readFileSync(BASELINE_PATH, 'utf8'))
const regResult = detectRegressions(current, baseline)
out.regressions = regResult.regressions
out.improvements = regResult.improvements
}
console.log(JSON.stringify(out, null, 2))
} else {
for (const [name, r] of Object.entries(results)) {
const cuts = r.alphaCuts
console.log(`${name}: mp=${r.mostPlausible.toFixed(4)}ms p95=[${cuts.p95.lower.toFixed(4)},${cuts.p95.upper.toFixed(4)}]`)
}
}
if (SAVE) {
const baseline = createBaseline([current])
fs.writeFileSync(BASELINE_PATH, JSON.stringify(baseline, null, 2), 'utf8')
console.log(`baseline saved: ${BASELINE_PATH}`)
} else if (fs.existsSync(BASELINE_PATH)) {
const baseline = JSON.parse(fs.readFileSync(BASELINE_PATH, 'utf8'))
const regResult = detectRegressions(current, baseline)
if (!AS_JSON) console.log(formatRegressions(regResult, 'pretty'))
// ── Ratio-based self-calibration ─────────────────────────────────────
// Absolute timings swing with machine load (a shared runner at load 19
// shifted every action +15..+50%). Comparing each action's RATIO to a cheap
// reference action cancels the load: load scales all actions proportionally,
// while a code regression shifts only the affected action's ratio. The
// reference action itself is still gate-checked absolutely with a loose
// bound (a regression of the reference would otherwise mask every ratio).
const RATIO_REFERENCE = process.env.BENCH_RATIO_REFERENCE || 'check[direct-hit]'
const RATIO_PERCENT = Number(process.env.RATIO_REGRESSION_PERCENT ?? 15)
const REFERENCE_PERCENT = Number(process.env.REFERENCE_REGRESSION_PERCENT ?? 30)
const currentRef = current.actions?.[RATIO_REFERENCE]?.mostPlausible
const baselineRef = baseline.actions?.[RATIO_REFERENCE]?.mostPlausible
const ratioViolations = []
let referenceViolation = false
if (currentRef > 0 && baselineRef > 0) {
if (currentRef > baselineRef * (1 + REFERENCE_PERCENT / 100)) {
referenceViolation = true
ratioViolations.push(
`${RATIO_REFERENCE} (reference) baseline=${baselineRef.toFixed(4)} → current=${currentRef.toFixed(4)} (+${(((currentRef / baselineRef) - 1) * 100).toFixed(1)}%)`
)
}
for (const [name, cur] of Object.entries(current.actions)) {
if (name === RATIO_REFERENCE) continue
const base = baseline.actions?.[name]
if (!base || !(base.mostPlausible > 0)) continue
const curRatio = cur.mostPlausible / currentRef
const baseRatio = base.mostPlausible / baselineRef
if (curRatio > baseRatio * (1 + RATIO_PERCENT / 100)) {
ratioViolations.push(
`${name} ratio ${curRatio.toFixed(3)} → baseline ${baseRatio.toFixed(3)} (+${(((curRatio / baseRatio) - 1) * 100).toFixed(1)}%)`
)
}
}
}
if (ratioViolations.length > 0) {
console.error(`${ratioViolations.length} ratio regression(s):`)
for (const v of ratioViolations) console.error(` - ${v}`)
if (referenceViolation) {
console.error(' (the reference action regressed absolutely — ratios may be unreliable)')
}
process.exit(1)
}
} else if (!SAVE) {
console.log('no baseline — first run, use --save')
}
if (CRASHED > 0) {
console.error(`${CRASHED} benchmark(s) crashed`)
process.exit(SAVE ? 0 : 2)
}