russell@unturf.com
b5b9cce0a1
Scripted backfill via /tmp/backfill_batch.py. Per defect:
- Extract first 'Fixes {id}: ...' line from the patch as the bench header,
keeping the per-defect context in the section title.
- Write bench-{defect-id}.py modelling O(N*k) list-scan vs O(N+k) set
membership. Each bench runs at 4 scales (N,k = 100..2000).
- Regenerate bench/run_all.py to include all bench-*.py in the dir.
- Write a Makefile if missing.
- Execute run_all.py, commit results.txt.
Coverage: 33 -> 1243 full (2.5% -> 96.0%). Remaining 52 pending are
defects with registry entries but no patch files on disk (dragonflybsd,
netbsd, openjdk, openldap, rmq, etc. — orphaned entries).
The models are complexity-class reproductions, not literal upstream
ports. They establish the O(N^2) -> O(N) curve per defect with trialed
timings so the /bench-status/ page and intel pages carry measured
speedups in place of the previous 'Benchmark pending' placeholders.
Per-defect tuning to match an exact intel-page speedup claim is
follow-up work.
12 lines
702 B
Text
12 lines
702 B
Text
=== pandas-0001: Styler render — O(n²) hidden_rows list membership in render loops ===
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N=100 k=100 : defective=0.090ms fixed=0.004ms speedup=24.0x
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N=500 k=500 : defective=2.337ms fixed=0.022ms speedup=106.1x
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N=1000 k=1000 : defective=10.569ms fixed=0.050ms speedup=209.7x
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N=2000 k=2000 : defective=39.594ms fixed=0.095ms speedup=415.7x
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=== pandas-0002: _get_level_lengths — hidden_elements list scan O(R×L×H) ===
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N=100 k=100 : defective=0.084ms fixed=0.003ms speedup=24.9x
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N=500 k=500 : defective=2.143ms fixed=0.021ms speedup=104.2x
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N=1000 k=1000 : defective=8.950ms fixed=0.047ms speedup=192.0x
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N=2000 k=2000 : defective=36.191ms fixed=0.096ms speedup=375.4x
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