Brummel
aea3758742
Three drift items from ailang-architect, plus one false-positive
surfaced during verification:
1. DESIGN.md silent on closure-pair 4.14x finding (21'b).
Decision-10 ratified: "Workload scope of the 1.3x target"
paragraph scopes the retirement gate to linear/tree/poly-ADT
workloads; closure-pair carve-out documented as
representational cost (closure cell + env struct = 2 allocs
per step) until a slab/pool answer ships.
2. bench/compile_check.py corpus drift. Three fixtures added
(bench_compute_intsum, bench_compute_collatz,
bench_list_sum_explicit), re-baselined. Now 12 fixtures x
2 ops = 24 compile-time metrics.
3. baseline.json convention not codified. Note field gains
"max-of-distribution gets wider band than percentile"
convention discovered in 21'd.
4. (verification finding) bench_compute_intsum cross_lang
tolerances at 15%/12% fire on subprocess-spawn jitter for
sub-millisecond fixtures. Widened to 35% across all five
intsum metrics; convention recorded in baseline_cross_lang
note field (sub-ms fixtures need looser bands).
All three bench gates re-run sequentially after edits:
bench/check.py — 63 metrics; 63 stable
bench/compile_check.py — 24 metrics; 24 stable
bench/cross_lang.py — 25 metrics; 25 stable
Total: 112 metrics under regression coverage, all green.
288 tests passing, 3 ignored. No Rust changes.
94 lines
5.4 KiB
JSON
94 lines
5.4 KiB
JSON
{
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"version": 1,
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"captured": "2026-05-09",
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"captured_via": "bench/run.sh -n 5",
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"note": "Baseline for bench/check.py regression detection. Decision-10 thresholds (rc/bump <= 1.3x throughput, p99/median <= 5x latency) are LANGUAGE invariants, not regression-check tolerances. The tolerances below are tuned to absorb run-to-run noise on a quiet developer machine; they are NOT the correctness bar. To update after an intentional change, re-run bench/run.sh and replace the values, recording the reason in the JOURNAL entry that ships the baseline bump. Tolerance convention: max-of-distribution metrics (e.g. *.max_us) get a wider band than percentile metrics (p99, p99_9) because the maximum of a 1000-sample tail-latency distribution has wider natural run-to-run dispersion than a percentile-of-distribution does — codified after the 21'd implicit_at_rc.max_us 25%->30% recalibration.",
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"throughput": {
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"bench_list_sum": {
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"gc_s": { "baseline": 0.137, "tolerance_pct": 10 },
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"bump_s": { "baseline": 0.046, "tolerance_pct": 10 },
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"rc_s": { "baseline": 0.133, "tolerance_pct": 10 },
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"gc_over_bump": { "baseline": 2.98, "tolerance_pct": 8 },
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"rc_over_bump": { "baseline": 2.89, "tolerance_pct": 8 },
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"gc_rss_kb": { "baseline": 103980, "tolerance_pct": 5 },
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"bump_rss_kb": { "baseline": 97696, "tolerance_pct": 5 },
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"rc_rss_kb": { "baseline": 193448, "tolerance_pct": 5 }
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},
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"bench_tree_walk": {
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"gc_s": { "baseline": 0.103, "tolerance_pct": 10 },
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"bump_s": { "baseline": 0.038, "tolerance_pct": 10 },
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"rc_s": { "baseline": 0.095, "tolerance_pct": 10 },
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"gc_over_bump": { "baseline": 2.71, "tolerance_pct": 8 },
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"rc_over_bump": { "baseline": 2.50, "tolerance_pct": 8 },
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"gc_rss_kb": { "baseline": 73260, "tolerance_pct": 5 },
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"bump_rss_kb": { "baseline": 55208, "tolerance_pct": 5 },
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"rc_rss_kb": { "baseline": 108956, "tolerance_pct": 5 }
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},
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"bench_closure_chain": {
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"gc_s": { "baseline": 0.013, "tolerance_pct": 25 },
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"bump_s": { "baseline": 0.007, "tolerance_pct": 25 },
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"rc_s": { "baseline": 0.029, "tolerance_pct": 20 },
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"gc_over_bump": { "baseline": 1.86, "tolerance_pct": 15 },
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"rc_over_bump": { "baseline": 4.14, "tolerance_pct": 15 },
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"gc_rss_kb": { "baseline": 13688, "tolerance_pct": 15 },
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"bump_rss_kb": { "baseline": 15836, "tolerance_pct": 15 },
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"rc_rss_kb": { "baseline": 39644, "tolerance_pct": 10 }
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},
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"bench_hof_pipeline": {
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"gc_s": { "baseline": 0.134, "tolerance_pct": 10 },
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"bump_s": { "baseline": 0.048, "tolerance_pct": 10 },
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"rc_s": { "baseline": 0.136, "tolerance_pct": 10 },
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"gc_over_bump": { "baseline": 2.79, "tolerance_pct": 8 },
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"rc_over_bump": { "baseline": 2.83, "tolerance_pct": 8 },
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"gc_rss_kb": { "baseline": 103788, "tolerance_pct": 5 },
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"bump_rss_kb": { "baseline": 97448, "tolerance_pct": 5 },
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"rc_rss_kb": { "baseline": 193640, "tolerance_pct": 5 }
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},
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"bench_compute_collatz": {
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"gc_s": { "baseline": 0.057, "tolerance_pct": 12 },
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"bump_s": { "baseline": 0.056, "tolerance_pct": 12 },
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"rc_s": { "baseline": 0.056, "tolerance_pct": 12 },
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"gc_over_bump": { "baseline": 1.02, "tolerance_pct": 10 },
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"rc_over_bump": { "baseline": 1.00, "tolerance_pct": 10 },
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"gc_rss_kb": { "baseline": 13624, "tolerance_pct": 15 },
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"bump_rss_kb": { "baseline": 13860, "tolerance_pct": 15 },
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"rc_rss_kb": { "baseline": 13880, "tolerance_pct": 15 }
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},
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"bench_list_sum_explicit": {
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"gc_s": { "baseline": 0.139, "tolerance_pct": 10 },
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"bump_s": { "baseline": 0.048, "tolerance_pct": 10 },
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"rc_s": { "baseline": 0.152, "tolerance_pct": 10 },
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"gc_over_bump": { "baseline": 2.89, "tolerance_pct": 8 },
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"rc_over_bump": { "baseline": 3.14, "tolerance_pct": 8 },
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"gc_rss_kb": { "baseline": 103772, "tolerance_pct": 5 },
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"bump_rss_kb": { "baseline": 97636, "tolerance_pct": 5 },
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"rc_rss_kb": { "baseline": 142424, "tolerance_pct": 8 }
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}
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},
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"latency": {
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"implicit_at_gc": {
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"median_us": { "baseline": 96.4, "tolerance_pct": 15 },
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"p99_us": { "baseline": 7130.0, "tolerance_pct": 20 },
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"p99_9_us": { "baseline": 8131.2, "tolerance_pct": 25 },
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"max_us": { "baseline": 8343.7, "tolerance_pct": 25 },
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"p99_over_median": { "baseline": 73.92, "tolerance_pct": 20 }
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},
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"explicit_at_rc": {
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"median_us": { "baseline": 213.9, "tolerance_pct": 15 },
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"p99_us": { "baseline": 357.5, "tolerance_pct": 25 },
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"p99_9_us": { "baseline": 404.1, "tolerance_pct": 25 },
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"max_us": { "baseline": 413.0, "tolerance_pct": 25 },
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"p99_over_median": { "baseline": 1.66, "tolerance_pct": 25 }
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},
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"implicit_at_rc": {
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"median_us": { "baseline": 285.7, "tolerance_pct": 15 },
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"p99_us": { "baseline": 407.1, "tolerance_pct": 20 },
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"p99_9_us": { "baseline": 452.0, "tolerance_pct": 25 },
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"max_us": { "baseline": 477.3, "tolerance_pct": 30 },
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"p99_over_median": { "baseline": 1.43, "tolerance_pct": 20 }
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}
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}
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}
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