{"abstract":"Row-group pruning reports physically empty groups as scan candidates.","category":"Data systems","checks":7,"contract":"Choose row groups that may satisfy an inclusive equality/range scan. Metadata [id,min,max,null_count,row_count] describes known integer values; unknown min/max cannot prove exclusion. Null-only and empty groups cannot satisfy a non-null range. Return candidate IDs without claiming every candidate contains a match.","contract_signature":"d","evaluation_group":"s3-data-systems-row-group-pruning","failed_approach":"Rejecting negative counts leaves empty metadata candidates intact.","family":"s3-data-systems-row-group-pruning-empty-group","id":"FA-45476","implementations":{"attempt":{"sha256":"7628976fa611b282f6ed4093005331764fd4d49352e7c09f43d5d28bf7c91e07","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    try:\n        groups,low,high=d\n        out=[]\n        for ident,minimum,maximum,nulls,count in groups:\n            if count<0: continue\n            if count>0 and nulls==count: continue\n            if minimum is not None and minimum>high: continue\n            if maximum is not None and maximum<low: continue\n            out.append(ident)\n        return out\n    except (IndexError, KeyError, ValueError, StopIteration) as exc:\n        return {\"representation_error\": type(exc).__name__}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nif N == 1:\n    check('inclusive low', solve([[[1, -1, 1, 0, 3]], 1, 3]), [1])\n    check('inclusive high', solve([[[1, 3, 5, 0, 3]], 1, 3]), [1])\n    check('missing minimum', solve([[[1, None, 3, 0, 3]], 1, 3]), [1])\n    check('missing maximum', solve([[[1, 1, None, 0, 3]], 1, 3]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 1, 3]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 1, 3]), [])\n    check('disjoint bounds', solve([[[1, -3, 0, 0, 3], [2, 4, 6, 0, 3]], 1, 3]), [])\nelif N == 2:\n    check('inclusive low', solve([[[1, 0, 2, 0, 3]], 2, 4]), [1])\n    check('inclusive high', solve([[[1, 4, 6, 0, 3]], 2, 4]), [1])\n    check('missing minimum', solve([[[1, None, 4, 0, 3]], 2, 4]), [1])\n    check('missing maximum', solve([[[1, 2, None, 0, 3]], 2, 4]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 2, 4]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 2, 4]), [])\n    check('disjoint bounds', solve([[[1, -2, 1, 0, 3], [2, 5, 7, 0, 3]], 2, 4]), [])\nelif N == 3:\n    check('inclusive low', solve([[[1, 1, 3, 0, 3]], 3, 5]), [1])\n    check('inclusive high', solve([[[1, 5, 7, 0, 3]], 3, 5]), [1])\n    check('missing minimum', solve([[[1, None, 5, 0, 3]], 3, 5]), [1])\n    check('missing maximum', solve([[[1, 3, None, 0, 3]], 3, 5]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 3, 5]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 3, 5]), [])\n    check('disjoint bounds', solve([[[1, -1, 2, 0, 3], [2, 6, 8, 0, 3]], 3, 5]), [])\nelif N == 4:\n    check('inclusive low', solve([[[1, 2, 4, 0, 3]], 4, 6]), [1])\n    check('inclusive high', solve([[[1, 6, 8, 0, 3]], 4, 6]), [1])\n    check('missing minimum', solve([[[1, None, 6, 0, 3]], 4, 6]), [1])\n    check('missing maximum', solve([[[1, 4, None, 0, 3]], 4, 6]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 4, 6]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 4, 6]), [])\n    check('disjoint bounds', solve([[[1, 0, 3, 0, 3], [2, 7, 9, 0, 3]], 4, 6]), [])\nelif N == 5:\n    check('inclusive low', solve([[[1, 3, 5, 0, 3]], 5, 7]), [1])\n    check('inclusive high', solve([[[1, 7, 9, 0, 3]], 5, 7]), [1])\n    check('missing minimum', solve([[[1, None, 7, 0, 3]], 5, 7]), [1])\n    check('missing maximum', solve([[[1, 5, None, 0, 3]], 5, 7]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 5, 7]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 5, 7]), [])\n    check('disjoint bounds', solve([[[1, 1, 4, 0, 3], [2, 8, 10, 0, 3]], 5, 7]), [])\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":"c5a177b227c4781239a1d3d86df3d98b5cddd0690ac6d5135ba248d165f8df69","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    try:\n        groups,low,high=d\n        out=[]\n        for ident,minimum,maximum,nulls,count in groups:\n            if count>0 and nulls==count: continue\n            if minimum is not None and minimum>high: continue\n            if maximum is not None and maximum<low: continue\n            out.append(ident)\n        return out\n    except (IndexError, KeyError, ValueError, StopIteration) as exc:\n        return {\"representation_error\": type(exc).__name__}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nif N == 1:\n    check('inclusive low', solve([[[1, -1, 1, 0, 3]], 1, 3]), [1])\n    check('inclusive high', solve([[[1, 3, 5, 0, 3]], 1, 3]), [1])\n    check('missing minimum', solve([[[1, None, 3, 0, 3]], 1, 3]), [1])\n    check('missing maximum', solve([[[1, 1, None, 0, 3]], 1, 3]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 1, 3]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 1, 3]), [])\n    check('disjoint bounds', solve([[[1, -3, 0, 0, 3], [2, 4, 6, 0, 3]], 1, 3]), [])\nelif N == 2:\n    check('inclusive low', solve([[[1, 0, 2, 0, 3]], 2, 4]), [1])\n    check('inclusive high', solve([[[1, 4, 6, 0, 3]], 2, 4]), [1])\n    check('missing minimum', solve([[[1, None, 4, 0, 3]], 2, 4]), [1])\n    check('missing maximum', solve([[[1, 2, None, 0, 3]], 2, 4]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 2, 4]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 2, 4]), [])\n    check('disjoint bounds', solve([[[1, -2, 1, 0, 3], [2, 5, 7, 0, 3]], 2, 4]), [])\nelif N == 3:\n    check('inclusive low', solve([[[1, 1, 3, 0, 3]], 3, 5]), [1])\n    check('inclusive high', solve([[[1, 5, 7, 0, 3]], 3, 5]), [1])\n    check('missing minimum', solve([[[1, None, 5, 0, 3]], 3, 5]), [1])\n    check('missing maximum', solve([[[1, 3, None, 0, 3]], 3, 5]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 3, 5]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 3, 5]), [])\n    check('disjoint bounds', solve([[[1, -1, 2, 0, 3], [2, 6, 8, 0, 3]], 3, 5]), [])\nelif N == 4:\n    check('inclusive low', solve([[[1, 2, 4, 0, 3]], 4, 6]), [1])\n    check('inclusive high', solve([[[1, 6, 8, 0, 3]], 4, 6]), [1])\n    check('missing minimum', solve([[[1, None, 6, 0, 3]], 4, 6]), [1])\n    check('missing maximum', solve([[[1, 4, None, 0, 3]], 4, 6]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 4, 6]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 4, 6]), [])\n    check('disjoint bounds', solve([[[1, 0, 3, 0, 3], [2, 7, 9, 0, 3]], 4, 6]), [])\nelif N == 5:\n    check('inclusive low', solve([[[1, 3, 5, 0, 3]], 5, 7]), [1])\n    check('inclusive high', solve([[[1, 7, 9, 0, 3]], 5, 7]), [1])\n    check('missing minimum', solve([[[1, None, 7, 0, 3]], 5, 7]), [1])\n    check('missing maximum', solve([[[1, 5, None, 0, 3]], 5, 7]), [1])\n    check('null only', solve([[[1, None, None, 3, 3]], 5, 7]), [])\n    check('empty group', solve([[[1, None, None, 0, 0]], 5, 7]), [])\n    check('disjoint bounds', solve([[[1, 1, 4, 0, 3], [2, 8, 10, 0, 3]], 5, 7]), [])\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":"Offline stipulated semantics over valid small inputs; no performance, concurrency, or production-engine 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-data-systems-row-group-pruning-empty-group","generated_at":"2026-09-29T14:44:22.629815+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A bounded deterministic data engine model makes representation and changelog faults reproducible.","root_cause":"row-group-pruning: Row-group pruning reports physically empty groups as scan candidates.","sha256":"321ce0e2a28b2712d7201c8a0e4f1f260c10f688af20fcccab5d1b2dc034370b","title":"Row-group pruning reports physically empty groups as scan candidates · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":44.716,"exit_code":1,"observations":[{"actual":[1],"check":"inclusive low","expected":[1],"passed":true},{"actual":[1],"check":"inclusive high","expected":[1],"passed":true},{"actual":[1],"check":"missing minimum","expected":[1],"passed":true},{"actual":[1],"check":"missing maximum","expected":[1],"passed":true},{"actual":[],"check":"null only","expected":[],"passed":true},{"actual":[1],"check":"empty group","expected":[],"passed":false},{"actual":[],"check":"disjoint bounds","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"inclusive low\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"inclusive high\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"missing minimum\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"missing maximum\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"null only\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty group\", \"actual\": [1], \"expected\": [], \"passed\": false}, {\"check\": \"disjoint bounds\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":46.476,"exit_code":1,"observations":[{"actual":[1],"check":"inclusive low","expected":[1],"passed":true},{"actual":[1],"check":"inclusive high","expected":[1],"passed":true},{"actual":[1],"check":"missing minimum","expected":[1],"passed":true},{"actual":[1],"check":"missing maximum","expected":[1],"passed":true},{"actual":[],"check":"null only","expected":[],"passed":true},{"actual":[1],"check":"empty group","expected":[],"passed":false},{"actual":[],"check":"disjoint bounds","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"inclusive low\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"inclusive high\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"missing minimum\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"missing maximum\", \"actual\": [1], \"expected\": [1], \"passed\": true}, {\"check\": \"null only\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty group\", \"actual\": [1], \"expected\": [], \"passed\": false}, {\"check\": \"disjoint bounds\", \"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."}}