russell@unturf.com
87503f60ef
Closes the three tractable pending buckets (all non-no_dir work):
+ lean4-0004..0007: 4 correctness/race benches (ir_interp DCL, jobreg
IO.Ref race, g_opts thread-local leakage, process envvar hash).
lean4-0007 shows 138x O(N^2)->O(N); 0004-0006 demonstrate lost
updates/leaks of several hundred in defective, 0 in fixed.
+ 0ad-0001..0004: 3 CWE-407 list.find->unordered_set speedup benches
(obstruction dirty shapes, modified entities, template cache) at
70-341x, plus 0ad-0004 log-redaction correctness at 100% redaction.
+ activemq-0001..0003: 3 CWE-407 benches (queue/topic consumer rotation,
demand-bridge candidate dedup, transaction-context endedXA set) at
95-178x.
+ linux-0001..0008: 8 Python complexity-class models for the kernel
patches. Coexist with the existing build-and-bench.sh kernel-level
bench; the Python models give 10-389x and the generator embeds them.
+ mercurial-0001-0001: standalone graphmod O(k^2)->O(k) model at
3-20x, alongside the existing bench_google_scale.py (which imports
the real mercurial graphmod).
Progress: 13 -> 33 full coverage. Remaining pending: 1262 no_dir +
12 non-CWE-407 race/leaked-context defects (future work on per-MOAD
bench templates).
60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
#!/usr/bin/env python3
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# bench-linux-0003.py
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# net/core/dev.c __dev_alloc_name: nested netdev_for_each_altname per device.
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# Models O(D*A) → O(D+A) via list-scan inside a loop vs set/dict lookup.
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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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"""Outer loop over N, inner linear list scan over K — O(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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accepted = []
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for x in items:
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if x in pool: # list __contains__ = O(K)
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accepted.append(x)
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# simulate nested work: scan pool to find position
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try:
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_ = pool.index(x)
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except ValueError:
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pass
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return time.perf_counter() - t0
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def bench_fixed(n, k):
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"""Outer loop over N, inner O(1) set/dict lookup."""
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pool = list(range(k))
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pool_set = set(pool)
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pool_pos = {v: i for i, v in enumerate(pool)}
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items = list(range(n))
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t0 = time.perf_counter()
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accepted = []
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for x in items:
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if x in pool_set: # O(1)
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accepted.append(x)
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_ = pool_pos.get(x) # O(1)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(100, 10), (500, 20), (1000, 30), (2000, 50)]
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def run():
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lines = []
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header = "=== linux-0003: dev.c __dev_alloc_name altname linear scan ==="
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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"D={n:<5} A={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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