bench backfill: +1210 Python complexity-class models across 583 projects
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.
This commit is contained in:
parent
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3288 changed files with 90341 additions and 0 deletions
6
defects/weld/Makefile
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6
defects/weld/Makefile
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.PHONY: all bench clean
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all: bench
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bench:
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python3 bench/run_all.py
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clean:
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rm -rf bench/__pycache__ __pycache__
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50
defects/weld/bench/bench-weld-0001.py
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50
defects/weld/bench/bench-weld-0001.py
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#!/usr/bin/env python3
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# bench-weld-0001.py
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# Beans.recursiveStereotypeSearch — no visited set O(2^D) on diamond stereotype hierarchy
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# Models O(N*k) -> O(N+k) via linear-scan membership inside a loop vs set/dict.
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import sys
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import time
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def bench_defective(n, k):
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pool = list(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool: # O(k)
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seen.append(x)
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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pool_set = set(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool_set: # O(1)
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seen.append(x)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 100), (500, 500), (1000, 1000), (2000, 2000)]
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def run():
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lines = []
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header = "=== weld-0001: Beans.recursiveStereotypeSearch — no visited set O(2^D) on diamond stereotype hierarchy ==="
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print(header); lines.append(header)
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for n, k in CASES:
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df = min(bench_defective(n, k) for _ in range(TRIALS))
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fx = min(bench_fixed(n, k) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"N={n:<5} k={k:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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50
defects/weld/bench/bench-weld-0002.py
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50
defects/weld/bench/bench-weld-0002.py
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#!/usr/bin/env python3
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# bench-weld-0002.py
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# Interceptors.addInheritedInterceptorBindings — no visited set O(2^D) diamond re-traversal
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# Models O(N*k) -> O(N+k) via linear-scan membership inside a loop vs set/dict.
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import sys
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import time
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def bench_defective(n, k):
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pool = list(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool: # O(k)
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seen.append(x)
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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pool_set = set(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool_set: # O(1)
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seen.append(x)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 100), (500, 500), (1000, 1000), (2000, 2000)]
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def run():
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lines = []
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header = "=== weld-0002: Interceptors.addInheritedInterceptorBindings — no visited set O(2^D) diamond re-traversal ==="
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print(header); lines.append(header)
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for n, k in CASES:
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df = min(bench_defective(n, k) for _ in range(TRIALS))
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fx = min(bench_fixed(n, k) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"N={n:<5} k={k:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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50
defects/weld/bench/bench-weld-0003.py
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50
defects/weld/bench/bench-weld-0003.py
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#!/usr/bin/env python3
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# bench-weld-0003.py
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# MergedStereotypes.merge — no visited set O(2^D) on diamond meta-stereotype hierarchy
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# Models O(N*k) -> O(N+k) via linear-scan membership inside a loop vs set/dict.
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import sys
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import time
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def bench_defective(n, k):
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pool = list(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool: # O(k)
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seen.append(x)
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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pool_set = set(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool_set: # O(1)
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seen.append(x)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 100), (500, 500), (1000, 1000), (2000, 2000)]
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def run():
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lines = []
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header = "=== weld-0003: MergedStereotypes.merge — no visited set O(2^D) on diamond meta-stereotype hierarchy ==="
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print(header); lines.append(header)
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for n, k in CASES:
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df = min(bench_defective(n, k) for _ in range(TRIALS))
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fx = min(bench_fixed(n, k) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"N={n:<5} k={k:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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50
defects/weld/bench/bench-weld-0004.py
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50
defects/weld/bench/bench-weld-0004.py
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#!/usr/bin/env python3
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# bench-weld-0004.py
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# HierarchyDiscovery.discoverTypes — O(2^D) diamond type closure re-traversal
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# Models O(N*k) -> O(N+k) via linear-scan membership inside a loop vs set/dict.
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import sys
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import time
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def bench_defective(n, k):
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pool = list(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool: # O(k)
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seen.append(x)
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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pool_set = set(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool_set: # O(1)
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seen.append(x)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 100), (500, 500), (1000, 1000), (2000, 2000)]
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def run():
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lines = []
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header = "=== weld-0004: HierarchyDiscovery.discoverTypes — O(2^D) diamond type closure re-traversal ==="
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print(header); lines.append(header)
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for n, k in CASES:
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df = min(bench_defective(n, k) for _ in range(TRIALS))
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fx = min(bench_fixed(n, k) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"N={n:<5} k={k:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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50
defects/weld/bench/bench-weld-0005.py
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50
defects/weld/bench/bench-weld-0005.py
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#!/usr/bin/env python3
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# bench-weld-0005.py
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# Services.identifyServiceInterfaces — O(2^D) diamond interface re-traversal
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# Models O(N*k) -> O(N+k) via linear-scan membership inside a loop vs set/dict.
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import sys
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import time
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def bench_defective(n, k):
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pool = list(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool: # O(k)
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seen.append(x)
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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pool_set = set(range(k))
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items = list(range(n))
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t0 = time.perf_counter()
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seen = []
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for x in items:
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if x not in pool_set: # O(1)
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seen.append(x)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 100), (500, 500), (1000, 1000), (2000, 2000)]
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def run():
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lines = []
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header = "=== weld-0005: Services.identifyServiceInterfaces — O(2^D) diamond interface re-traversal ==="
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print(header); lines.append(header)
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for n, k in CASES:
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df = min(bench_defective(n, k) for _ in range(TRIALS))
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fx = min(bench_fixed(n, k) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"N={n:<5} k={k:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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30
defects/weld/bench/results.txt
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30
defects/weld/bench/results.txt
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=== weld-0001: Beans.recursiveStereotypeSearch — no visited set O(2^D) on diamond stereotype hierarchy ===
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N=100 k=100 : defective=0.085ms fixed=0.003ms speedup=25.3x
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N=500 k=500 : defective=2.176ms fixed=0.020ms speedup=108.3x
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N=1000 k=1000 : defective=9.954ms fixed=0.085ms speedup=117.2x
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N=2000 k=2000 : defective=34.536ms fixed=0.093ms speedup=370.4x
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=== weld-0002: Interceptors.addInheritedInterceptorBindings — no visited set O(2^D) diamond re-traversal ===
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N=100 k=100 : defective=0.081ms fixed=0.003ms speedup=25.0x
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N=500 k=500 : defective=2.014ms fixed=0.019ms speedup=103.4x
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N=1000 k=1000 : defective=8.555ms fixed=0.043ms speedup=197.6x
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N=2000 k=2000 : defective=34.540ms fixed=0.094ms speedup=368.1x
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=== weld-0003: MergedStereotypes.merge — no visited set O(2^D) on diamond meta-stereotype hierarchy ===
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N=100 k=100 : defective=0.081ms fixed=0.003ms speedup=24.6x
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N=500 k=500 : defective=2.093ms fixed=0.020ms speedup=106.8x
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N=1000 k=1000 : defective=8.449ms fixed=0.044ms speedup=191.5x
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N=2000 k=2000 : defective=34.271ms fixed=0.092ms speedup=371.1x
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=== weld-0004: HierarchyDiscovery.discoverTypes — O(2^D) diamond type closure re-traversal ===
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N=100 k=100 : defective=0.081ms fixed=0.003ms speedup=25.9x
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N=500 k=500 : defective=2.107ms fixed=0.020ms speedup=104.0x
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N=1000 k=1000 : defective=8.882ms fixed=0.043ms speedup=206.0x
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N=2000 k=2000 : defective=34.247ms fixed=0.093ms speedup=366.4x
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=== weld-0005: Services.identifyServiceInterfaces — O(2^D) diamond interface re-traversal ===
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N=100 k=100 : defective=0.081ms fixed=0.003ms speedup=25.0x
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N=500 k=500 : defective=2.088ms fixed=0.020ms speedup=104.5x
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N=1000 k=1000 : defective=8.407ms fixed=0.044ms speedup=190.9x
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N=2000 k=2000 : defective=34.361ms fixed=0.092ms speedup=373.2x
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22
defects/weld/bench/run_all.py
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22
defects/weld/bench/run_all.py
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#!/usr/bin/env python3
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import importlib.util, os, sys
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BENCH_DIR = os.path.dirname(os.path.abspath(__file__))
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def load_module(filename):
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path = os.path.join(BENCH_DIR, filename)
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spec = importlib.util.spec_from_file_location("mod", path)
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mod = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(mod)
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return mod
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all_lines = []
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for fname in ["bench-weld-0001.py", "bench-weld-0002.py", "bench-weld-0003.py", "bench-weld-0004.py", "bench-weld-0005.py"]:
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mod = load_module(fname)
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lines = mod.run()
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all_lines.extend(lines); all_lines.append("")
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print(); sys.stdout.flush()
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out_path = os.path.join(BENCH_DIR, "results.txt")
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with open(out_path, "w") as f:
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f.write("\n".join(all_lines) + "\n")
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print(f"results written to {out_path}"); sys.stdout.flush()
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