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.
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=== sqlalchemy-0001: CWE-407: list-scan inside loop in sqlalchemy-0001 (generic model) ===
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N=100 k=100 : defective=0.093ms fixed=0.004ms speedup=24.8x
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N=500 k=500 : defective=2.370ms fixed=0.023ms speedup=104.0x
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N=1000 k=1000 : defective=9.689ms fixed=0.050ms speedup=195.0x
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N=2000 k=2000 : defective=36.622ms fixed=0.097ms speedup=378.6x
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=== sqlalchemy-0002: CWE-407: list-scan inside loop in sqlalchemy-0002 (generic model) ===
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N=100 k=100 : defective=0.084ms fixed=0.003ms speedup=25.5x
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N=500 k=500 : defective=2.145ms fixed=0.020ms speedup=106.0x
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N=1000 k=1000 : defective=8.599ms fixed=0.045ms speedup=192.9x
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N=2000 k=2000 : defective=35.183ms fixed=0.096ms speedup=365.1x
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=== sqlalchemy-0003: evaluated_keys list → set in _apply_evaluators() ===
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N=100 k=100 : defective=0.086ms fixed=0.003ms speedup=25.3x
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N=500 k=500 : defective=2.091ms fixed=0.020ms speedup=102.3x
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N=1000 k=1000 : defective=13.135ms fixed=0.094ms speedup=140.3x
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N=2000 k=2000 : defective=35.309ms fixed=0.096ms speedup=368.6x
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