{"abstract":"A missing parameter shard silently shortens reconstruction.","category":"Distributed training aggregation","checks":6,"contract":"Given shards [start, values] and total length, return concatenated values only when intervals exactly cover the range once; otherwise None.","contract_signature":"shards, total","evaluation_group":"w3-dta-shard-gap-detection","failed_approach":"Checking only the final covered length accepts interior gaps paired with overlaps.","family":"w3-distributed-training-aggregation-shard-gap-detection","id":"FA-99271","implementations":{"attempt":{"sha256":"43899a2e8e6f90c74897b1c6c582744e9e57fc79813980941ff204a5caf4a9eb","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(shards, total):\n    out=[]; end=0\n    for s,a in sorted(shards):\n        if s<end: return None\n        out.extend(a); end=s+len(a)\n    return out if end==total else None\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('complete split',solve([[2,[2,3]],[0,[0,1]]],4),[0,1,2,3])\ncheck('interior gap overlap disguise',solve([[0,[0,1,2]],[2,[2,3]]],4),None)\ncheck('leading gap',solve([[1,[1]]],2),None)\ncheck('trailing gap',solve([[0,[0]]],2),None)\ncheck('empty exact tensor',solve([],0),[])\ncheck('empty with expected values',solve([],1),None)\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":"7fbf4630d31e7cfc594a6a55ae47fd807f45f2513e27287d0f7059a87a8540c1","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(shards, total):\n    return [v for s,a in sorted(shards) for v in a]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('complete split',solve([[2,[2,3]],[0,[0,1]]],4),[0,1,2,3])\ncheck('interior gap overlap disguise',solve([[0,[0,1,2]],[2,[2,3]]],4),None)\ncheck('leading gap',solve([[1,[1]]],2),None)\ncheck('trailing gap',solve([[0,[0]]],2),None)\ncheck('empty exact tensor',solve([],0),[])\ncheck('empty with expected values',solve([],1),None)\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":"Inputs are already materialized Python values from a fixed toy collective; no transport, failure recovery, optimizer state, or real model behavior is represented. 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-distributed-training-aggregation-shard-gap-detection","generated_at":"2026-09-30T16:48:22.178703+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A toy distributed-training contract makes replica and shard contribution rules explicit without claiming framework compatibility or performance.","root_cause":"Concatenation alone cannot distinguish a complete tensor from a transfer with a gap.","sha256":"1bcc1a2757f3b57bf7d19ebada483cbd5cda092456a4061b726b4d54959a1584","title":"A missing parameter shard silently shortens reconstruction · case 01","variant":1,"variant_policy":"The same explicitly authored fixtures repeat across all five numbered records; runtime N is unused. These records share one mechanism and must remain together in evaluation splits.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":30.766,"exit_code":1,"observations":[{"actual":[0,1,2,3],"check":"complete split","expected":[0,1,2,3],"passed":true},{"actual":null,"check":"interior gap overlap disguise","expected":null,"passed":true},{"actual":[1],"check":"leading gap","expected":null,"passed":false},{"actual":null,"check":"trailing gap","expected":null,"passed":true},{"actual":[],"check":"empty exact tensor","expected":[],"passed":true},{"actual":null,"check":"empty with expected values","expected":null,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"complete split\", \"actual\": [0, 1, 2, 3], \"expected\": [0, 1, 2, 3], \"passed\": true}, {\"check\": \"interior gap overlap disguise\", \"actual\": null, \"expected\": null, \"passed\": true}, {\"check\": \"leading gap\", \"actual\": [1], \"expected\": null, \"passed\": false}, {\"check\": \"trailing gap\", \"actual\": null, \"expected\": null, \"passed\": true}, {\"check\": \"empty exact tensor\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty with expected values\", \"actual\": null, \"expected\": null, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":29.204,"exit_code":1,"observations":[{"actual":[0,1,2,3],"check":"complete split","expected":[0,1,2,3],"passed":true},{"actual":[0,1,2,2,3],"check":"interior gap overlap disguise","expected":null,"passed":false},{"actual":[1],"check":"leading gap","expected":null,"passed":false},{"actual":[0],"check":"trailing gap","expected":null,"passed":false},{"actual":[],"check":"empty exact tensor","expected":[],"passed":true},{"actual":[],"check":"empty with expected values","expected":null,"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"complete split\", \"actual\": [0, 1, 2, 3], \"expected\": [0, 1, 2, 3], \"passed\": true}, {\"check\": \"interior gap overlap disguise\", \"actual\": [0, 1, 2, 2, 3], \"expected\": null, \"passed\": false}, {\"check\": \"leading gap\", \"actual\": [1], \"expected\": null, \"passed\": false}, {\"check\": \"trailing gap\", \"actual\": [0], \"expected\": null, \"passed\": false}, {\"check\": \"empty exact tensor\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty with expected values\", \"actual\": [], \"expected\": null, \"passed\": false}], \"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."}}