{"abstract":"column reduction confuses row positions with column indices.","category":"Sparse tensor canonicalization","checks":6,"contract":"Return a dense list of width column sums, adding each value at its stored column.","contract_signature":"columns,values,width","evaluation_group":"w3-sparse-tensor-canonicalization-csr-column-sum","failed_approach":"A strict prefix count still excludes contributions whose label equals the output column.","family":"w3-sparse-tensor-canonicalization-csr-column-sum","id":"FA-100481","implementations":{"attempt":{"sha256":"51096166fd0a58b053951bff3b15c59ed82007bcd00dd79e48050f53189bb378","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(columns,values,width):\n    return [sum(v for c,v in zip(columns,values) if c<j) for j in range(width)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('reordered columns',solve([2,0,2],[N,3,4],3),[3,0,N+4])\ncheck('empty columns',solve([],[],N),[0]*N)\ncheck('single bucket',solve([0],[7],1),[7])\ncheck('repeated bucket',solve([1,1],[N,2],3),[0,N+2,0])\ncheck('negative contribution',solve([0,2],[-N,5],3),[-N,0,5])\ncheck('no entries',solve([],[],0),[])\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":"1d8bf771690e3e8bd5451803bd7d0c5878d11b51b031718a5f3fdd37eda0a307","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(columns,values,width):\n    return [sum(values[i] for i,c in enumerate(columns) if i==j) for j in range(width)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('reordered columns',solve([2,0,2],[N,3,4],3),[3,0,N+4])\ncheck('empty columns',solve([],[],N),[0]*N)\ncheck('single bucket',solve([0],[7],1),[7])\ncheck('repeated bucket',solve([1,1],[N,2],3),[0,N+2,0])\ncheck('negative contribution',solve([0,2],[-N,5],3),[-N,0,5])\ncheck('no entries',solve([],[],0),[])\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":"These are toy integer-valued COO or CSR contracts; they make no claim about a framework API, floating point policy, or large tensor performance. 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":"w3-sparse-tensor-canonicalization-csr-column-sum","generated_at":"2026-09-30T16:48:36.241690+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A small offline sparse-array operation has explicit coordinate and storage semantics.","root_cause":"Coordinate values are accumulated into output positions determined by their column labels, not their storage index.","sha256":"547dc1722b40b1bba6eebe1b5f798d0b627c45eba93ff11acf743bb6ec7d48f9","title":"Sparse tensor: column reduction confuses row positions with column indices · case 01","variant":1,"variant_policy":"The fixture code references N, supplied as 1 through 5. Fixed boundary checks may repeat. These records share one mechanism and must remain together in evaluation splits.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":29.161,"exit_code":1,"observations":[{"actual":[0,3,3],"check":"reordered columns","expected":[3,0,5],"passed":false},{"actual":[0],"check":"empty columns","expected":[0],"passed":true},{"actual":[0],"check":"single bucket","expected":[7],"passed":false},{"actual":[0,0,3],"check":"repeated bucket","expected":[0,3,0],"passed":false},{"actual":[0,-1,-1],"check":"negative contribution","expected":[-1,0,5],"passed":false},{"actual":[],"check":"no entries","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"reordered columns\", \"actual\": [0, 3, 3], \"expected\": [3, 0, 5], \"passed\": false}, {\"check\": \"empty columns\", \"actual\": [0], \"expected\": [0], \"passed\": true}, {\"check\": \"single bucket\", \"actual\": [0], \"expected\": [7], \"passed\": false}, {\"check\": \"repeated bucket\", \"actual\": [0, 0, 3], \"expected\": [0, 3, 0], \"passed\": false}, {\"check\": \"negative contribution\", \"actual\": [0, -1, -1], \"expected\": [-1, 0, 5], \"passed\": false}, {\"check\": \"no entries\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":28.558,"exit_code":1,"observations":[{"actual":[1,3,4],"check":"reordered columns","expected":[3,0,5],"passed":false},{"actual":[0],"check":"empty columns","expected":[0],"passed":true},{"actual":[7],"check":"single bucket","expected":[7],"passed":true},{"actual":[1,2,0],"check":"repeated bucket","expected":[0,3,0],"passed":false},{"actual":[-1,5,0],"check":"negative contribution","expected":[-1,0,5],"passed":false},{"actual":[],"check":"no entries","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"reordered columns\", \"actual\": [1, 3, 4], \"expected\": [3, 0, 5], \"passed\": false}, {\"check\": \"empty columns\", \"actual\": [0], \"expected\": [0], \"passed\": true}, {\"check\": \"single bucket\", \"actual\": [7], \"expected\": [7], \"passed\": true}, {\"check\": \"repeated bucket\", \"actual\": [1, 2, 0], \"expected\": [0, 3, 0], \"passed\": false}, {\"check\": \"negative contribution\", \"actual\": [-1, 5, 0], \"expected\": [-1, 0, 5], \"passed\": false}, {\"check\": \"no entries\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}