russell@unturf.com
d67ec93a5d
vitest-0001: coverage-v8 coverage.result.find inside merged.result.forEach -> Map<url, result> lookup. Bench: 824x at N=M=10000 coverage entries. testng-0001: DynamicGraph.toDot freeNodes.contains inside two for-each loops -> Map<T, String> color lookup via getOrDefault. Bench: 64x at N=2000. jasmine-0001: SpyRegistry.spyOnAllFunctions propertiesToSkip.indexOf inside Array.filter + .concat growth across D prototype levels -> Set.has + O(1) growth. Bench: 61x at D=10, P=300. check-0001: libcheck suite_tcase linear strcmp scan over tclst List -> parallel hashtable for O(1) lookup amortized. Bench: 117x at N=1000. Shipped as design sketch; full integration requires companion hashtable. Also ships whitepaper/outreach/test-harness-survey.md documenting 14 clean-scan frameworks across Clojure, OCaml, Haskell, Erlang, Go, F#, Julia, Shell, Lua, JS. Scope covered 61 targets across 30+ languages. UNDF IDs: 1292 (check), 1293 (jasmine), 1294 (testng), 1295 (vitest). All 12 tests pass.
80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
#!/usr/bin/env python3
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# UNDF: UNDF-2026-000001293 (jasmine-0001)
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#
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# CWE-407: Algorithmic Complexity
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#
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# Defect:
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# jasmine-0001: SpyRegistry.spyOnAllFunctions walks prototype chain,
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# filtering via propertiesToSkip.indexOf(prop) inside an
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# Array.filter + concat. For chain depth D with P properties
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# per level, cost is O(D * P^2).
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#
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# Fix:
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# Replace propertiesToSkip Array with Set; filter lookup and growth both
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# O(1). Total cost drops to O(D * P).
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#
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# Complexity gate (from bench/results.txt):
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# D=10, P=300: defective=54ms, fixed=0.9ms (61x).
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# Fixed must complete in <5ms at D=5, P=200. k-scaling <17.5x.
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import importlib.util, os, sys, unittest
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HERE = os.path.dirname(os.path.abspath(__file__))
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BENCH = os.path.join(os.path.dirname(HERE), "bench")
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sys.path.insert(0, BENCH)
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def _load(fname):
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path = os.path.join(BENCH, fname)
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spec = importlib.util.spec_from_file_location(fname, 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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_mod = _load("bench-jasmine-0001.py")
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class TestJasmine0001Correctness(unittest.TestCase):
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def test_set_filter_matches_list_indexof_filter(self):
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# Both filters should produce the same surviving set of properties
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seen_list = []
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seen_set = set()
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levels = [
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["a", "b", "c"],
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["b", "c", "d", "e"], # b, c are duplicates
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["d", "e", "f", "g"],
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]
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result_list = []
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result_set = []
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for level in levels:
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new_list = [p for p in level if p not in seen_list]
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seen_list = seen_list + new_list
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result_list.extend(new_list)
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new_set = [p for p in level if p not in seen_set]
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for p in new_set:
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seen_set.add(p)
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result_set.extend(new_set)
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self.assertEqual(result_list, result_set)
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self.assertEqual(result_set, ["a", "b", "c", "d", "e", "f", "g"])
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class TestJasmine0001ComplexityGate(unittest.TestCase):
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def test_fixed_wallclock_D5_P200(self):
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t_s = min(_mod.bench_fixed(5, 200) for _ in range(3))
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self.assertLess(t_s * 1000, 5.0,
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f"fixed took {t_s*1000:.3f}ms at D=5 P=200, expected <5ms")
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def test_fixed_scaling_linear(self):
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t_small = min(_mod.bench_fixed(5, 100) for _ in range(3))
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t_large = min(_mod.bench_fixed(5, 500) for _ in range(3))
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ratio = t_large / t_small if t_small > 0 else float("inf")
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# 5x P-scaling should remain <17.5x (O(P), not O(P^2))
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self.assertLess(ratio, 17.5,
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f"fixed P=500/P=100 ratio {ratio:.2f}x, expected <17.5x")
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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