{"abstract":"The reduction disagrees with its explicit aggregation oracle.","category":"Numerical aggregation","checks":8,"contract":"Return multiset Jaccard similarity: sum of per-label minimum frequencies divided by sum of per-label maximum frequencies, as exact Fraction string. Both empty returns \"1\". Integer labels are nominal.","evaluation_group":"s3-na-multiset-overlap-similarity","failed_approach":"Using only first-sample labels still omits second-only mass.","family":"s3-numerical-aggregation-multiset-overlap-similarity-overlap-label-intersection","id":"FA-14081","implementations":{"attempt":{"sha256":"8bfa3737f16b32440befe1212d0d7010da752b9c5245ff1fa12e98c76f980fda","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nfrom collections import Counter, defaultdict\nimport math\nimport itertools\nN = 1\nobservations = []\ndef solve(a, b):\n    ca,cb=Counter(a),Counter(b)\n    keys=set(ca)\n    intersection=sum(min(ca[k],cb[k]) for k in keys)\n    union=sum(max(ca[k],cb[k]) for k in keys)\n    return str(Fraction(intersection,union)) if union else \"1\"\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('regression 1', solve(*([1, 1, 1, 2], [1, 2, 2])), '2/5')\ncheck('regression 2', solve(*([], [])), '1')\ncheck('regression 3', solve(*([1, 2], [])), '0')\ncheck('regression 4', solve(*([2, 2], [2, 2])), '1')\ncheck('regression 5', solve(*([-1, 0, 0], [0, 1])), '1/4')\ncheck('regression 6', solve(*([3, 3, 4], [3, 3, 3, 4, 4])), '3/5')\ncheck('regression 7', solve(*([0], [1])), '0')\ncheck(\"variable overlap mass\",solve([0]*N,[0]*(N+1)),str(Fraction(N,N+1)))\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"845eb773d24e47f08eb960c46444ded74776538db4061b2f984938862944e579","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nfrom collections import Counter, defaultdict\nimport math\nimport itertools\nN = 1\nobservations = []\ndef solve(a, b):\n    ca,cb=Counter(a),Counter(b)\n    keys=set(ca)&set(cb)\n    intersection=sum(min(ca[k],cb[k]) for k in keys)\n    union=sum(max(ca[k],cb[k]) for k in keys)\n    return str(Fraction(intersection,union)) if union else \"1\"\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('regression 1', solve(*([1, 1, 1, 2], [1, 2, 2])), '2/5')\ncheck('regression 2', solve(*([], [])), '1')\ncheck('regression 3', solve(*([1, 2], [])), '0')\ncheck('regression 4', solve(*([2, 2], [2, 2])), '1')\ncheck('regression 5', solve(*([-1, 0, 0], [0, 1])), '1/4')\ncheck('regression 6', solve(*([3, 3, 4], [3, 3, 3, 4, 4])), '3/5')\ncheck('regression 7', solve(*([0], [1])), '0')\ncheck(\"variable overlap mass\",solve([0]*N,[0]*(N+1)),str(Fraction(N,N+1)))\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"3b051b777280386b7ee69a79a8c64dcf88848d0b2840a6fbc9eeaf9db68094be","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nfrom collections import Counter, defaultdict\nimport math\nimport itertools\nN = 1\nobservations = []\ndef solve(a, b):\n    ca,cb=Counter(a),Counter(b)\n    keys=set(ca)|set(cb)\n    intersection=sum(min(ca[k],cb[k]) for k in keys)\n    union=sum(max(ca[k],cb[k]) for k in keys)\n    return str(Fraction(intersection,union)) if union else \"1\"\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('regression 1', solve(*([1, 1, 1, 2], [1, 2, 2])), '2/5')\ncheck('regression 2', solve(*([], [])), '1')\ncheck('regression 3', solve(*([1, 2], [])), '0')\ncheck('regression 4', solve(*([2, 2], [2, 2])), '1')\ncheck('regression 5', solve(*([-1, 0, 0], [0, 1])), '1/4')\ncheck('regression 6', solve(*([3, 3, 4], [3, 3, 3, 4, 4])), '3/5')\ncheck('regression 7', solve(*([0], [1])), '0')\ncheck(\"variable overlap mass\",solve([0]*N,[0]*(N+1)),str(Fraction(N,N+1)))\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Small offline integer/rational inputs only; no performance, statistical inference, or production-library conformance claim. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"s3-numerical-aggregation-multiset-overlap-similarity-overlap-label-intersection","generated_at":"2026-09-29T14:39:13.421861+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Exact bounded examples isolate a reduction defect without floating-point or external-service effects.","repair":"Preserve the multiset overlap similarity contract at the identified reduction decision.","root_cause":"Union mass is calculated only on shared labels.","sha256":"95f64eaa20419bacb23f8e81df3227dbd130d321efa31c90a2dbb1425d947d10","title":"Multiset overlap similarity: Union mass is calculated only on shared labels. · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":44.112,"exit_code":1,"observations":[{"actual":"2/5","check":"regression 1","expected":"2/5","passed":true},{"actual":"1","check":"regression 2","expected":"1","passed":true},{"actual":"0","check":"regression 3","expected":"0","passed":true},{"actual":"1","check":"regression 4","expected":"1","passed":true},{"actual":"1/3","check":"regression 5","expected":"1/4","passed":false},{"actual":"3/5","check":"regression 6","expected":"3/5","passed":true},{"actual":"0","check":"regression 7","expected":"0","passed":true},{"actual":"1/2","check":"variable overlap mass","expected":"1/2","passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 1\", \"actual\": \"2/5\", \"expected\": \"2/5\", \"passed\": true}, {\"check\": \"regression 2\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 3\", \"actual\": \"0\", \"expected\": \"0\", \"passed\": true}, {\"check\": \"regression 4\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 5\", \"actual\": \"1/3\", \"expected\": \"1/4\", \"passed\": false}, {\"check\": \"regression 6\", \"actual\": \"3/5\", \"expected\": \"3/5\", \"passed\": true}, {\"check\": \"regression 7\", \"actual\": \"0\", \"expected\": \"0\", \"passed\": true}, {\"check\": \"variable overlap mass\", \"actual\": \"1/2\", \"expected\": \"1/2\", \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":44.805,"exit_code":1,"observations":[{"actual":"2/5","check":"regression 1","expected":"2/5","passed":true},{"actual":"1","check":"regression 2","expected":"1","passed":true},{"actual":"1","check":"regression 3","expected":"0","passed":false},{"actual":"1","check":"regression 4","expected":"1","passed":true},{"actual":"1/2","check":"regression 5","expected":"1/4","passed":false},{"actual":"3/5","check":"regression 6","expected":"3/5","passed":true},{"actual":"1","check":"regression 7","expected":"0","passed":false},{"actual":"1/2","check":"variable overlap mass","expected":"1/2","passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 1\", \"actual\": \"2/5\", \"expected\": \"2/5\", \"passed\": true}, {\"check\": \"regression 2\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 3\", \"actual\": \"1\", \"expected\": \"0\", \"passed\": false}, {\"check\": \"regression 4\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 5\", \"actual\": \"1/2\", \"expected\": \"1/4\", \"passed\": false}, {\"check\": \"regression 6\", \"actual\": \"3/5\", \"expected\": \"3/5\", \"passed\": true}, {\"check\": \"regression 7\", \"actual\": \"1\", \"expected\": \"0\", \"passed\": false}, {\"check\": \"variable overlap mass\", \"actual\": \"1/2\", \"expected\": \"1/2\", \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":44.756,"exit_code":0,"observations":[{"actual":"2/5","check":"regression 1","expected":"2/5","passed":true},{"actual":"1","check":"regression 2","expected":"1","passed":true},{"actual":"0","check":"regression 3","expected":"0","passed":true},{"actual":"1","check":"regression 4","expected":"1","passed":true},{"actual":"1/4","check":"regression 5","expected":"1/4","passed":true},{"actual":"3/5","check":"regression 6","expected":"3/5","passed":true},{"actual":"0","check":"regression 7","expected":"0","passed":true},{"actual":"1/2","check":"variable overlap mass","expected":"1/2","passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 1\", \"actual\": \"2/5\", \"expected\": \"2/5\", \"passed\": true}, {\"check\": \"regression 2\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 3\", \"actual\": \"0\", \"expected\": \"0\", \"passed\": true}, {\"check\": \"regression 4\", \"actual\": \"1\", \"expected\": \"1\", \"passed\": true}, {\"check\": \"regression 5\", \"actual\": \"1/4\", \"expected\": \"1/4\", \"passed\": true}, {\"check\": \"regression 6\", \"actual\": \"3/5\", \"expected\": \"3/5\", \"passed\": true}, {\"check\": \"regression 7\", \"actual\": \"0\", \"expected\": \"0\", \"passed\": true}, {\"check\": \"variable overlap mass\", \"actual\": \"1/2\", \"expected\": \"1/2\", \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}