{"abstract":"column projection returns all entries instead of one column.","category":"Sparse tensor canonicalization","checks":6,"contract":"Project a COO matrix onto one column and return sorted [row,value] pairs.","contract_signature":"entries,column","evaluation_group":"w3-sparse-tensor-canonicalization-coo-column-filter","failed_approach":"A prefix of columns still contains values from other columns.","family":"w3-sparse-tensor-canonicalization-coo-column-filter","id":"FA-100506","implementations":{"attempt":{"sha256":"3c9ccb52d211ec19b2b009d097661877ba362e8d8c0d292f78eba7f786802f3a","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(entries,column):\n    return [[r,v] for r,c,v in entries if c<=column]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('one column',solve([[0,0,2],[1,N,3],[2,N+1,4]],N),[[1,3]])\ncheck('empty',solve([],N),[])\ncheck('absent',solve([[0,0,5]],N+1),[])\ncheck('multiple rows',solve([[2,N,8],[0,N,3],[1,0,2]],N),[[0,3],[2,8]])\ncheck('column zero',solve([[N,0,6],[0,1,7]],0),[[N,6]])\ncheck('singleton',solve([[0,N,4]],N),[[0,4]])\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":"4dd919ed67d7fa63b4bba9b5bd0a7326d75ff7c015e2b87262053793c19ee909","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(entries,column):\n    return [[r,v] for r,c,v in entries]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('one column',solve([[0,0,2],[1,N,3],[2,N+1,4]],N),[[1,3]])\ncheck('empty',solve([],N),[])\ncheck('absent',solve([[0,0,5]],N+1),[])\ncheck('multiple rows',solve([[2,N,8],[0,N,3],[1,0,2]],N),[[0,3],[2,8]])\ncheck('column zero',solve([[N,0,6],[0,1,7]],0),[[N,6]])\ncheck('singleton',solve([[0,N,4]],N),[[0,4]])\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-coo-column-filter","generated_at":"2026-09-30T16:48:36.272325+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":"Projection should select one exact column and retain each matching row/value.","sha256":"a9326c8525597856b4484b2b073d2c7b2e372ceda103ff6f86808921ccd91fc2","title":"Sparse tensor: column projection returns all entries instead of one column · 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":28.899,"exit_code":1,"observations":[{"actual":[[0,2],[1,3]],"check":"one column","expected":[[1,3]],"passed":false},{"actual":[],"check":"empty","expected":[],"passed":true},{"actual":[[0,5]],"check":"absent","expected":[],"passed":false},{"actual":[[2,8],[0,3],[1,2]],"check":"multiple rows","expected":[[0,3],[2,8]],"passed":false},{"actual":[[1,6]],"check":"column zero","expected":[[1,6]],"passed":true},{"actual":[[0,4]],"check":"singleton","expected":[[0,4]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"one column\", \"actual\": [[0, 2], [1, 3]], \"expected\": [[1, 3]], \"passed\": false}, {\"check\": \"empty\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"absent\", \"actual\": [[0, 5]], \"expected\": [], \"passed\": false}, {\"check\": \"multiple rows\", \"actual\": [[2, 8], [0, 3], [1, 2]], \"expected\": [[0, 3], [2, 8]], \"passed\": false}, {\"check\": \"column zero\", \"actual\": [[1, 6]], \"expected\": [[1, 6]], \"passed\": true}, {\"check\": \"singleton\", \"actual\": [[0, 4]], \"expected\": [[0, 4]], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":28.091,"exit_code":1,"observations":[{"actual":[[0,2],[1,3],[2,4]],"check":"one column","expected":[[1,3]],"passed":false},{"actual":[],"check":"empty","expected":[],"passed":true},{"actual":[[0,5]],"check":"absent","expected":[],"passed":false},{"actual":[[2,8],[0,3],[1,2]],"check":"multiple rows","expected":[[0,3],[2,8]],"passed":false},{"actual":[[1,6],[0,7]],"check":"column zero","expected":[[1,6]],"passed":false},{"actual":[[0,4]],"check":"singleton","expected":[[0,4]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"one column\", \"actual\": [[0, 2], [1, 3], [2, 4]], \"expected\": [[1, 3]], \"passed\": false}, {\"check\": \"empty\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"absent\", \"actual\": [[0, 5]], \"expected\": [], \"passed\": false}, {\"check\": \"multiple rows\", \"actual\": [[2, 8], [0, 3], [1, 2]], \"expected\": [[0, 3], [2, 8]], \"passed\": false}, {\"check\": \"column zero\", \"actual\": [[1, 6], [0, 7]], \"expected\": [[1, 6]], \"passed\": false}, {\"check\": \"singleton\", \"actual\": [[0, 4]], \"expected\": [[0, 4]], \"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."}}