{"abstract":"Unpivot removes explicitly stored null field values.","category":"Data systems","checks":7,"contract":"Unpivot selected columns of record dictionaries into [id,column,value] rows. Include explicitly present None values, skip absent columns, respect requested column order and repetitions, and retain parent row order.","evaluation_group":"s3-data-systems-unpivot-presence","failed_approach":"Truthiness additionally discards stored zero values.","family":"s3-data-systems-unpivot-presence-explicit-null","id":"FA-44916","implementations":{"attempt":{"sha256":"e127dd6381964724d824a6e81fac0f435cb6edc12694db371537aba55a18111c","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    try:\n        rows,columns=d\n        result=[]\n        for row in rows:\n            ident=row['id']\n            for column in columns:\n                if column not in row: continue\n                if row.get(column): result.append([ident,column,row.get(column)])\n        return result\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('source column order', solve([[{'id': 9, 'a': 1, 'b': 2}], ['b', 'a']]), [[9, 'b', 2], [9, 'a', 1]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 1}], ['a', 'b']]), [[9, 'a', 1]])\n    check('duplicate column', solve([[{'id': 9, 'a': 1}], ['a', 'a']]), [[9, 'a', 1], [9, 'a', 1]])\n    check('parent order', solve([[{'id': 9, 'a': 1}, {'id': 2, 'a': 2}], ['a']]), [[9, 'a', 1], [2, 'a', 2]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 1}], []]), [])\nelif N == 2:\n    check('source column order', solve([[{'id': 9, 'a': 2, 'b': 3}], ['b', 'a']]), [[9, 'b', 3], [9, 'a', 2]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 2}], ['a', 'b']]), [[9, 'a', 2]])\n    check('duplicate column', solve([[{'id': 9, 'a': 2}], ['a', 'a']]), [[9, 'a', 2], [9, 'a', 2]])\n    check('parent order', solve([[{'id': 9, 'a': 2}, {'id': 2, 'a': 3}], ['a']]), [[9, 'a', 2], [2, 'a', 3]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 2}], []]), [])\nelif N == 3:\n    check('source column order', solve([[{'id': 9, 'a': 3, 'b': 4}], ['b', 'a']]), [[9, 'b', 4], [9, 'a', 3]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 3}], ['a', 'b']]), [[9, 'a', 3]])\n    check('duplicate column', solve([[{'id': 9, 'a': 3}], ['a', 'a']]), [[9, 'a', 3], [9, 'a', 3]])\n    check('parent order', solve([[{'id': 9, 'a': 3}, {'id': 2, 'a': 4}], ['a']]), [[9, 'a', 3], [2, 'a', 4]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 3}], []]), [])\nelif N == 4:\n    check('source column order', solve([[{'id': 9, 'a': 4, 'b': 5}], ['b', 'a']]), [[9, 'b', 5], [9, 'a', 4]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 4}], ['a', 'b']]), [[9, 'a', 4]])\n    check('duplicate column', solve([[{'id': 9, 'a': 4}], ['a', 'a']]), [[9, 'a', 4], [9, 'a', 4]])\n    check('parent order', solve([[{'id': 9, 'a': 4}, {'id': 2, 'a': 5}], ['a']]), [[9, 'a', 4], [2, 'a', 5]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 4}], []]), [])\nelif N == 5:\n    check('source column order', solve([[{'id': 9, 'a': 5, 'b': 6}], ['b', 'a']]), [[9, 'b', 6], [9, 'a', 5]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 5}], ['a', 'b']]), [[9, 'a', 5]])\n    check('duplicate column', solve([[{'id': 9, 'a': 5}], ['a', 'a']]), [[9, 'a', 5], [9, 'a', 5]])\n    check('parent order', solve([[{'id': 9, 'a': 5}, {'id': 2, 'a': 6}], ['a']]), [[9, 'a', 5], [2, 'a', 6]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 5}], []]), [])\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":"958d016389d1e24734fd91eef3e5eae6e7168b8846efa39eb0a0d0e0b6319ce7","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    try:\n        rows,columns=d\n        result=[]\n        for row in rows:\n            ident=row['id']\n            for column in columns:\n                if column not in row: continue\n                if row.get(column) is not None: result.append([ident,column,row.get(column)])\n        return result\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('source column order', solve([[{'id': 9, 'a': 1, 'b': 2}], ['b', 'a']]), [[9, 'b', 2], [9, 'a', 1]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 1}], ['a', 'b']]), [[9, 'a', 1]])\n    check('duplicate column', solve([[{'id': 9, 'a': 1}], ['a', 'a']]), [[9, 'a', 1], [9, 'a', 1]])\n    check('parent order', solve([[{'id': 9, 'a': 1}, {'id': 2, 'a': 2}], ['a']]), [[9, 'a', 1], [2, 'a', 2]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 1}], []]), [])\nelif N == 2:\n    check('source column order', solve([[{'id': 9, 'a': 2, 'b': 3}], ['b', 'a']]), [[9, 'b', 3], [9, 'a', 2]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 2}], ['a', 'b']]), [[9, 'a', 2]])\n    check('duplicate column', solve([[{'id': 9, 'a': 2}], ['a', 'a']]), [[9, 'a', 2], [9, 'a', 2]])\n    check('parent order', solve([[{'id': 9, 'a': 2}, {'id': 2, 'a': 3}], ['a']]), [[9, 'a', 2], [2, 'a', 3]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 2}], []]), [])\nelif N == 3:\n    check('source column order', solve([[{'id': 9, 'a': 3, 'b': 4}], ['b', 'a']]), [[9, 'b', 4], [9, 'a', 3]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 3}], ['a', 'b']]), [[9, 'a', 3]])\n    check('duplicate column', solve([[{'id': 9, 'a': 3}], ['a', 'a']]), [[9, 'a', 3], [9, 'a', 3]])\n    check('parent order', solve([[{'id': 9, 'a': 3}, {'id': 2, 'a': 4}], ['a']]), [[9, 'a', 3], [2, 'a', 4]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 3}], []]), [])\nelif N == 4:\n    check('source column order', solve([[{'id': 9, 'a': 4, 'b': 5}], ['b', 'a']]), [[9, 'b', 5], [9, 'a', 4]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 4}], ['a', 'b']]), [[9, 'a', 4]])\n    check('duplicate column', solve([[{'id': 9, 'a': 4}], ['a', 'a']]), [[9, 'a', 4], [9, 'a', 4]])\n    check('parent order', solve([[{'id': 9, 'a': 4}, {'id': 2, 'a': 5}], ['a']]), [[9, 'a', 4], [2, 'a', 5]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 4}], []]), [])\nelif N == 5:\n    check('source column order', solve([[{'id': 9, 'a': 5, 'b': 6}], ['b', 'a']]), [[9, 'b', 6], [9, 'a', 5]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 5}], ['a', 'b']]), [[9, 'a', 5]])\n    check('duplicate column', solve([[{'id': 9, 'a': 5}], ['a', 'a']]), [[9, 'a', 5], [9, 'a', 5]])\n    check('parent order', solve([[{'id': 9, 'a': 5}, {'id': 2, 'a': 6}], ['a']]), [[9, 'a', 5], [2, 'a', 6]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 5}], []]), [])\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":"2592dbe1cfc06f8759d015f54a779497ffd4c343e9df5850a67920e5a3b57bd0","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    try:\n        rows,columns=d\n        result=[]\n        for row in rows:\n            ident=row['id']\n            for column in columns:\n                if column not in row: continue\n                result.append([ident,column,row.get(column)])\n        return result\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('source column order', solve([[{'id': 9, 'a': 1, 'b': 2}], ['b', 'a']]), [[9, 'b', 2], [9, 'a', 1]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 1}], ['a', 'b']]), [[9, 'a', 1]])\n    check('duplicate column', solve([[{'id': 9, 'a': 1}], ['a', 'a']]), [[9, 'a', 1], [9, 'a', 1]])\n    check('parent order', solve([[{'id': 9, 'a': 1}, {'id': 2, 'a': 2}], ['a']]), [[9, 'a', 1], [2, 'a', 2]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 1}], []]), [])\nelif N == 2:\n    check('source column order', solve([[{'id': 9, 'a': 2, 'b': 3}], ['b', 'a']]), [[9, 'b', 3], [9, 'a', 2]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 2}], ['a', 'b']]), [[9, 'a', 2]])\n    check('duplicate column', solve([[{'id': 9, 'a': 2}], ['a', 'a']]), [[9, 'a', 2], [9, 'a', 2]])\n    check('parent order', solve([[{'id': 9, 'a': 2}, {'id': 2, 'a': 3}], ['a']]), [[9, 'a', 2], [2, 'a', 3]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 2}], []]), [])\nelif N == 3:\n    check('source column order', solve([[{'id': 9, 'a': 3, 'b': 4}], ['b', 'a']]), [[9, 'b', 4], [9, 'a', 3]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 3}], ['a', 'b']]), [[9, 'a', 3]])\n    check('duplicate column', solve([[{'id': 9, 'a': 3}], ['a', 'a']]), [[9, 'a', 3], [9, 'a', 3]])\n    check('parent order', solve([[{'id': 9, 'a': 3}, {'id': 2, 'a': 4}], ['a']]), [[9, 'a', 3], [2, 'a', 4]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 3}], []]), [])\nelif N == 4:\n    check('source column order', solve([[{'id': 9, 'a': 4, 'b': 5}], ['b', 'a']]), [[9, 'b', 5], [9, 'a', 4]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 4}], ['a', 'b']]), [[9, 'a', 4]])\n    check('duplicate column', solve([[{'id': 9, 'a': 4}], ['a', 'a']]), [[9, 'a', 4], [9, 'a', 4]])\n    check('parent order', solve([[{'id': 9, 'a': 4}, {'id': 2, 'a': 5}], ['a']]), [[9, 'a', 4], [2, 'a', 5]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 4}], []]), [])\nelif N == 5:\n    check('source column order', solve([[{'id': 9, 'a': 5, 'b': 6}], ['b', 'a']]), [[9, 'b', 6], [9, 'a', 5]])\n    check('explicit null', solve([[{'id': 9, 'a': None}], ['a']]), [[9, 'a', None]])\n    check('missing field', solve([[{'id': 9, 'a': 5}], ['a', 'b']]), [[9, 'a', 5]])\n    check('duplicate column', solve([[{'id': 9, 'a': 5}], ['a', 'a']]), [[9, 'a', 5], [9, 'a', 5]])\n    check('parent order', solve([[{'id': 9, 'a': 5}, {'id': 2, 'a': 6}], ['a']]), [[9, 'a', 5], [2, 'a', 6]])\n    check('zero value', solve([[{'id': 9, 'a': 0}], ['a']]), [[9, 'a', 0]])\n    check('empty projection', solve([[{'id': 9, 'a': 5}], []]), [])\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-unpivot-presence-explicit-null","generated_at":"2026-09-29T14:44:16.932744+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.","repair":"Preserve the stated physical representation and operation order: Unpivot selected columns of record dictionaries into [id,column,value] rows. Include explicitly present None values, skip absent columns, respect requested column order and repetitions, and retain parent row order.","root_cause":"unpivot-presence: Unpivot removes explicitly stored null field values.","sha256":"43339ee99ae80909a6ecad23772d19e37725ac0108bc1929fc7cc9927143fc41","title":"Unpivot removes explicitly stored null field values · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":46.203,"exit_code":1,"observations":[{"actual":[[9,"b",2],[9,"a",1]],"check":"source column order","expected":[[9,"b",2],[9,"a",1]],"passed":true},{"actual":[],"check":"explicit null","expected":[[9,"a",null]],"passed":false},{"actual":[[9,"a",1]],"check":"missing field","expected":[[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[9,"a",1]],"check":"duplicate column","expected":[[9,"a",1],[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[2,"a",2]],"check":"parent order","expected":[[9,"a",1],[2,"a",2]],"passed":true},{"actual":[],"check":"zero value","expected":[[9,"a",0]],"passed":false},{"actual":[],"check":"empty projection","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"source column order\", \"actual\": [[9, \"b\", 2], [9, \"a\", 1]], \"expected\": [[9, \"b\", 2], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"explicit null\", \"actual\": [], \"expected\": [[9, \"a\", null]], \"passed\": false}, {\"check\": \"missing field\", \"actual\": [[9, \"a\", 1]], \"expected\": [[9, \"a\", 1]], \"passed\": true}, {\"check\": \"duplicate column\", \"actual\": [[9, \"a\", 1], [9, \"a\", 1]], \"expected\": [[9, \"a\", 1], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"parent order\", \"actual\": [[9, \"a\", 1], [2, \"a\", 2]], \"expected\": [[9, \"a\", 1], [2, \"a\", 2]], \"passed\": true}, {\"check\": \"zero value\", \"actual\": [], \"expected\": [[9, \"a\", 0]], \"passed\": false}, {\"check\": \"empty projection\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.207,"exit_code":1,"observations":[{"actual":[[9,"b",2],[9,"a",1]],"check":"source column order","expected":[[9,"b",2],[9,"a",1]],"passed":true},{"actual":[],"check":"explicit null","expected":[[9,"a",null]],"passed":false},{"actual":[[9,"a",1]],"check":"missing field","expected":[[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[9,"a",1]],"check":"duplicate column","expected":[[9,"a",1],[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[2,"a",2]],"check":"parent order","expected":[[9,"a",1],[2,"a",2]],"passed":true},{"actual":[[9,"a",0]],"check":"zero value","expected":[[9,"a",0]],"passed":true},{"actual":[],"check":"empty projection","expected":[],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"source column order\", \"actual\": [[9, \"b\", 2], [9, \"a\", 1]], \"expected\": [[9, \"b\", 2], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"explicit null\", \"actual\": [], \"expected\": [[9, \"a\", null]], \"passed\": false}, {\"check\": \"missing field\", \"actual\": [[9, \"a\", 1]], \"expected\": [[9, \"a\", 1]], \"passed\": true}, {\"check\": \"duplicate column\", \"actual\": [[9, \"a\", 1], [9, \"a\", 1]], \"expected\": [[9, \"a\", 1], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"parent order\", \"actual\": [[9, \"a\", 1], [2, \"a\", 2]], \"expected\": [[9, \"a\", 1], [2, \"a\", 2]], \"passed\": true}, {\"check\": \"zero value\", \"actual\": [[9, \"a\", 0]], \"expected\": [[9, \"a\", 0]], \"passed\": true}, {\"check\": \"empty projection\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":40.522,"exit_code":0,"observations":[{"actual":[[9,"b",2],[9,"a",1]],"check":"source column order","expected":[[9,"b",2],[9,"a",1]],"passed":true},{"actual":[[9,"a",null]],"check":"explicit null","expected":[[9,"a",null]],"passed":true},{"actual":[[9,"a",1]],"check":"missing field","expected":[[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[9,"a",1]],"check":"duplicate column","expected":[[9,"a",1],[9,"a",1]],"passed":true},{"actual":[[9,"a",1],[2,"a",2]],"check":"parent order","expected":[[9,"a",1],[2,"a",2]],"passed":true},{"actual":[[9,"a",0]],"check":"zero value","expected":[[9,"a",0]],"passed":true},{"actual":[],"check":"empty projection","expected":[],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"source column order\", \"actual\": [[9, \"b\", 2], [9, \"a\", 1]], \"expected\": [[9, \"b\", 2], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"explicit null\", \"actual\": [[9, \"a\", null]], \"expected\": [[9, \"a\", null]], \"passed\": true}, {\"check\": \"missing field\", \"actual\": [[9, \"a\", 1]], \"expected\": [[9, \"a\", 1]], \"passed\": true}, {\"check\": \"duplicate column\", \"actual\": [[9, \"a\", 1], [9, \"a\", 1]], \"expected\": [[9, \"a\", 1], [9, \"a\", 1]], \"passed\": true}, {\"check\": \"parent order\", \"actual\": [[9, \"a\", 1], [2, \"a\", 2]], \"expected\": [[9, \"a\", 1], [2, \"a\", 2]], \"passed\": true}, {\"check\": \"zero value\", \"actual\": [[9, \"a\", 0]], \"expected\": [[9, \"a\", 0]], \"passed\": true}, {\"check\": \"empty projection\", \"actual\": [], \"expected\": [], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}