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.
Beam: exhaustive scan of sdks/java/core + runners — all membership tests already
use proper Set types (HashSet, LinkedHashSet, ImmutableSet, TreeSet). CLEAN.
Hive hive-0001: SharedWorkOptimizer.mergeSchema() uses List.contains() in loops
for neededColumnIDs/neededColumns/virtualCols dedup. O(D*R) per list. MEDIUM, 3-4x.
Hive hive-0002: HiveRelMdSize.averageColumnSizes() uses ImmutableList.contains(i)
in column loop during Calcite metadata queries. O(C*L). MEDIUM, 3-5x.
Both patched with HashSet wrappers. 2/2 unit tests PASS.
Authors: russell@unturf.com · brackishbert@gmail.com · foxhop.net · TimeHexOn.com
Patches, unit tests, benchmarks, whitepaper, and outreach briefs.
Public domain — no copyright claimed. Use freely.
