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.
openxcom-0001: AIModule _reachable/_reachableWithAttack std::vector<int>
with std::find() inside AI loops (setupAmbush, setupEscape,
selectPointNearTarget, findFirePoint). O(N*R) per alien turn where
N = nodes checked, R = reachable tiles (~500 on typical map).
Fix: std::unordered_set<int> for O(1) lookup. MEDIUM-HIGH, 7.6x.
openxcom-0002: SavedGame::isResearched linear scan of _discovered vector
O(D) per call, called O(R*4) times from getAvailableResearchProjects
per base. Also unlocked vector with std::find O(R*U).
Fix: parallel unordered_set<string> for O(1) lookup. MEDIUM, 4.5x.
MOAD-0002 (Intertangle): CLEAN, typical game state architecture
MOAD-0003 (Leaked Context): CLEAN, single-threaded game
MOAD-0004 (Logged Secret): CLEAN, no credentials
MOAD-0005 (Thundering Herd): CLEAN, no concurrent caching
