{"abstract":"The decoded time state disagrees with the explicit regression oracle for floor.","category":"Time representation","checks":11,"contract":"A presentation clock preserves monotonic output while exposing raw wall coordinate and rollback debt. It advances a floor by monotonic elapsed since previous sample; publish max(raw wall,floor) if continuity mode enabled, otherwise raw wall. On explicit reset, discard old floor. Output adjusted coordinate, added bias, rollback marker, debt, source mode and next checkpoint. Negative elapsed invalidates sample.","evaluation_group":"s3-time-wall_rollback_presentation","failed_approach":"The partial correction still substitutes r['last_output'] + max(0,elapsed) at the same fault site.","family":"s3-time_representation-wall-rollback-presentation-floor","id":"FA-18601","implementations":{"attempt":{"sha256":"768aa0d914353a51809e1f08f341d3d64176c57d97e1e6ef96c87caf17079d72","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(r):\n    elapsed = r['mono'] - r['last_mono']\n    valid = elapsed >= 0\n    floor = r['last_output'] + max(0,elapsed)\n    rollback = r['wall'] < floor\n    output = max(r['wall'],floor) if r['continuous'] else r['wall']\n    bias = output - r['wall']\n    debt = max(0,floor - r['wall'])\n    mode = 'floor' if r['continuous'] and rollback else 'wall'\n    checkpoint_output = output if valid else r['last_output']\n    checkpoint_mono = r['mono'] if valid else r['last_mono']\n    return [valid,output,bias,debt,mode,[checkpoint_output,checkpoint_mono],rollback]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('fixture 1', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 5, 5, 'floor', [110, 20], True])\ncheck('fixture 2', solve({'mono': 20, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 120, 0, 0, 'wall', [120, 20], False])\ncheck('fixture 3', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 2}), [True, 105, 0, 5, 'wall', [105, 20], True])\ncheck('fixture 4', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': True, 'continuous': True, 'last_bias': 2}), [True, 90, 0, 0, 'wall', [90, 20], False])\ncheck('fixture 5', solve({'mono': 10, 'last_mono': 10, 'wall': 100, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 100, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 6', solve({'mono': 9, 'last_mono': 10, 'wall': 101, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [False, 101, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 7', solve({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 0, 0, 'wall', [110, 20], False])\ncheck('fixture 8', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 20, 20, 'floor', [110, 20], True])\ncheck('fixture 9', solve({'mono': 30, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 5}), [True, 120, 15, 15, 'floor', [120, 30], True])\ncheck('fixture 10', solve({'mono': 10, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 0}), [True, 120, 0, 0, 'wall', [120, 10], False])\nvariant = [({'mono': 20, 'last_mono': 10, 'wall': 106, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 4, 4, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 107, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 3, 3, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 108, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 2, 2, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 109, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 1, 1, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 0, 0, 'wall', [110, 20], False])]\ncheck(\"variant capture\", solve(variant[N-1][0]), variant[N-1][1])\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":"86950f09327de075c0ac3aef55d893deef1c49554cea89f32fd587cc87f0dc6e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(r):\n    elapsed = r['mono'] - r['last_mono']\n    valid = elapsed >= 0\n    floor = r['last_output']\n    rollback = r['wall'] < floor\n    output = max(r['wall'],floor) if r['continuous'] else r['wall']\n    bias = output - r['wall']\n    debt = max(0,floor - r['wall'])\n    mode = 'floor' if r['continuous'] and rollback else 'wall'\n    checkpoint_output = output if valid else r['last_output']\n    checkpoint_mono = r['mono'] if valid else r['last_mono']\n    return [valid,output,bias,debt,mode,[checkpoint_output,checkpoint_mono],rollback]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('fixture 1', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 5, 5, 'floor', [110, 20], True])\ncheck('fixture 2', solve({'mono': 20, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 120, 0, 0, 'wall', [120, 20], False])\ncheck('fixture 3', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 2}), [True, 105, 0, 5, 'wall', [105, 20], True])\ncheck('fixture 4', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': True, 'continuous': True, 'last_bias': 2}), [True, 90, 0, 0, 'wall', [90, 20], False])\ncheck('fixture 5', solve({'mono': 10, 'last_mono': 10, 'wall': 100, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 100, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 6', solve({'mono': 9, 'last_mono': 10, 'wall': 101, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [False, 101, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 7', solve({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 0, 0, 'wall', [110, 20], False])\ncheck('fixture 8', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 20, 20, 'floor', [110, 20], True])\ncheck('fixture 9', solve({'mono': 30, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 5}), [True, 120, 15, 15, 'floor', [120, 30], True])\ncheck('fixture 10', solve({'mono': 10, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 0}), [True, 120, 0, 0, 'wall', [120, 10], False])\nvariant = [({'mono': 20, 'last_mono': 10, 'wall': 106, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 4, 4, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 107, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 3, 3, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 108, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 2, 2, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 109, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 1, 1, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 0, 0, 'wall', [110, 20], False])]\ncheck(\"variant capture\", solve(variant[N-1][0]), variant[N-1][1])\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":"2c419a3c37a871fe92299030de8da56be0bad1440e620cff4008e5f3bdf9b4de","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(r):\n    elapsed = r['mono'] - r['last_mono']\n    valid = elapsed >= 0\n    floor = r['wall'] if r['reset'] else r['last_output'] + max(0,elapsed)\n    rollback = r['wall'] < floor\n    output = max(r['wall'],floor) if r['continuous'] else r['wall']\n    bias = output - r['wall']\n    debt = max(0,floor - r['wall'])\n    mode = 'floor' if r['continuous'] and rollback else 'wall'\n    checkpoint_output = output if valid else r['last_output']\n    checkpoint_mono = r['mono'] if valid else r['last_mono']\n    return [valid,output,bias,debt,mode,[checkpoint_output,checkpoint_mono],rollback]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('fixture 1', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 5, 5, 'floor', [110, 20], True])\ncheck('fixture 2', solve({'mono': 20, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 120, 0, 0, 'wall', [120, 20], False])\ncheck('fixture 3', solve({'mono': 20, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 2}), [True, 105, 0, 5, 'wall', [105, 20], True])\ncheck('fixture 4', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': True, 'continuous': True, 'last_bias': 2}), [True, 90, 0, 0, 'wall', [90, 20], False])\ncheck('fixture 5', solve({'mono': 10, 'last_mono': 10, 'wall': 100, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 100, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 6', solve({'mono': 9, 'last_mono': 10, 'wall': 101, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [False, 101, 0, 0, 'wall', [100, 10], False])\ncheck('fixture 7', solve({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 0, 0, 'wall', [110, 20], False])\ncheck('fixture 8', solve({'mono': 20, 'last_mono': 10, 'wall': 90, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}), [True, 110, 20, 20, 'floor', [110, 20], True])\ncheck('fixture 9', solve({'mono': 30, 'last_mono': 10, 'wall': 105, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 5}), [True, 120, 15, 15, 'floor', [120, 30], True])\ncheck('fixture 10', solve({'mono': 10, 'last_mono': 10, 'wall': 120, 'last_output': 100, 'reset': False, 'continuous': False, 'last_bias': 0}), [True, 120, 0, 0, 'wall', [120, 10], False])\nvariant = [({'mono': 20, 'last_mono': 10, 'wall': 106, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 4, 4, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 107, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 3, 3, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 108, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 2, 2, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 109, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 1, 1, 'floor', [110, 20], True]), ({'mono': 20, 'last_mono': 10, 'wall': 110, 'last_output': 100, 'reset': False, 'continuous': True, 'last_bias': 2}, [True, 110, 0, 0, 'wall', [110, 20], False])]\ncheck(\"variant capture\", solve(variant[N-1][0]), variant[N-1][1])\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":"Deterministic integer reference model with stipulated units and policies; not a complete clock, wire standard or platform implementation. 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-time_representation-wall-rollback-presentation-floor","generated_at":"2026-09-29T14:39:59.230897+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Clock transfer and timestamp consumers require preserved coordinate, phase, validity and elapsed-time semantics.","repair":"Preserve the declared coordinate and state contract at floor: floor = r['wall'] if r['reset'] else r['last_output'] + max(0,elapsed).","root_cause":"Monotonic floor stops advancing or survives explicit reset.","sha256":"445407bf65295ff99fa5d6aa7b44e359c3b59ba995d4aab16f741684638bb039","title":"Monotonic floor stops advancing or survives explicit reset · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":43.338,"exit_code":1,"observations":[{"actual":[true,110,5,5,"floor",[110,20],true],"check":"fixture 1","expected":[true,110,5,5,"floor",[110,20],true],"passed":true},{"actual":[true,120,0,0,"wall",[120,20],false],"check":"fixture 2","expected":[true,120,0,0,"wall",[120,20],false],"passed":true},{"actual":[true,105,0,5,"wall",[105,20],true],"check":"fixture 3","expected":[true,105,0,5,"wall",[105,20],true],"passed":true},{"actual":[true,110,20,20,"floor",[110,20],true],"check":"fixture 4","expected":[true,90,0,0,"wall",[90,20],false],"passed":false},{"actual":[true,100,0,0,"wall",[100,10],false],"check":"fixture 5","expected":[true,100,0,0,"wall",[100,10],false],"passed":true},{"actual":[false,101,0,0,"wall",[100,10],false],"check":"fixture 6","expected":[false,101,0,0,"wall",[100,10],false],"passed":true},{"actual":[true,110,0,0,"wall",[110,20],false],"check":"fixture 7","expected":[true,110,0,0,"wall",[110,20],false],"passed":true},{"actual":[true,110,20,20,"floor",[110,20],true],"check":"fixture 8","expected":[true,110,20,20,"floor",[110,20],true],"passed":true},{"actual":[true,120,15,15,"floor",[120,30],true],"check":"fixture 9","expected":[true,120,15,15,"floor",[120,30],true],"passed":true},{"actual":[true,120,0,0,"wall",[120,10],false],"check":"fixture 10","expected":[true,120,0,0,"wall",[120,10],false],"passed":true},{"actual":[true,110,4,4,"floor",[110,20],true],"check":"variant capture","expected":[true,110,4,4,"floor",[110,20],true],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fixture 1\", \"actual\": [true, 110, 5, 5, \"floor\", [110, 20], true], \"expected\": [true, 110, 5, 5, \"floor\", [110, 20], true], \"passed\": true}, {\"check\": \"fixture 2\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"passed\": true}, {\"check\": \"fixture 3\", \"actual\": [true, 105, 0, 5, \"wall\", [105, 20], true], \"expected\": [true, 105, 0, 5, \"wall\", [105, 20], true], \"passed\": true}, {\"check\": \"fixture 4\", \"actual\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"expected\": [true, 90, 0, 0, \"wall\", [90, 20], false], \"passed\": false}, {\"check\": \"fixture 5\", \"actual\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"expected\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 6\", \"actual\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"expected\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 7\", \"actual\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"expected\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"passed\": true}, {\"check\": \"fixture 8\", \"actual\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"expected\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"passed\": true}, {\"check\": \"fixture 9\", \"actual\": [true, 120, 15, 15, \"floor\", [120, 30], true], \"expected\": [true, 120, 15, 15, \"floor\", [120, 30], true], \"passed\": true}, {\"check\": \"fixture 10\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"passed\": true}, {\"check\": \"variant capture\", \"actual\": [true, 110, 4, 4, \"floor\", [110, 20], true], \"expected\": [true, 110, 4, 4, \"floor\", [110, 20], true], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.894,"exit_code":1,"observations":[{"actual":[true,105,0,0,"wall",[105,20],false],"check":"fixture 1","expected":[true,110,5,5,"floor",[110,20],true],"passed":false},{"actual":[true,120,0,0,"wall",[120,20],false],"check":"fixture 2","expected":[true,120,0,0,"wall",[120,20],false],"passed":true},{"actual":[true,105,0,0,"wall",[105,20],false],"check":"fixture 3","expected":[true,105,0,5,"wall",[105,20],true],"passed":false},{"actual":[true,100,10,10,"floor",[100,20],true],"check":"fixture 4","expected":[true,90,0,0,"wall",[90,20],false],"passed":false},{"actual":[true,100,0,0,"wall",[100,10],false],"check":"fixture 5","expected":[true,100,0,0,"wall",[100,10],false],"passed":true},{"actual":[false,101,0,0,"wall",[100,10],false],"check":"fixture 6","expected":[false,101,0,0,"wall",[100,10],false],"passed":true},{"actual":[true,110,0,0,"wall",[110,20],false],"check":"fixture 7","expected":[true,110,0,0,"wall",[110,20],false],"passed":true},{"actual":[true,100,10,10,"floor",[100,20],true],"check":"fixture 8","expected":[true,110,20,20,"floor",[110,20],true],"passed":false},{"actual":[true,105,0,0,"wall",[105,30],false],"check":"fixture 9","expected":[true,120,15,15,"floor",[120,30],true],"passed":false},{"actual":[true,120,0,0,"wall",[120,10],false],"check":"fixture 10","expected":[true,120,0,0,"wall",[120,10],false],"passed":true},{"actual":[true,106,0,0,"wall",[106,20],false],"check":"variant capture","expected":[true,110,4,4,"floor",[110,20],true],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fixture 1\", \"actual\": [true, 105, 0, 0, \"wall\", [105, 20], false], \"expected\": [true, 110, 5, 5, \"floor\", [110, 20], true], \"passed\": false}, {\"check\": \"fixture 2\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"passed\": true}, {\"check\": \"fixture 3\", \"actual\": [true, 105, 0, 0, \"wall\", [105, 20], false], \"expected\": [true, 105, 0, 5, \"wall\", [105, 20], true], \"passed\": false}, {\"check\": \"fixture 4\", \"actual\": [true, 100, 10, 10, \"floor\", [100, 20], true], \"expected\": [true, 90, 0, 0, \"wall\", [90, 20], false], \"passed\": false}, {\"check\": \"fixture 5\", \"actual\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"expected\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 6\", \"actual\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"expected\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 7\", \"actual\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"expected\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"passed\": true}, {\"check\": \"fixture 8\", \"actual\": [true, 100, 10, 10, \"floor\", [100, 20], true], \"expected\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"passed\": false}, {\"check\": \"fixture 9\", \"actual\": [true, 105, 0, 0, \"wall\", [105, 30], false], \"expected\": [true, 120, 15, 15, \"floor\", [120, 30], true], \"passed\": false}, {\"check\": \"fixture 10\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"passed\": true}, {\"check\": \"variant capture\", \"actual\": [true, 106, 0, 0, \"wall\", [106, 20], false], \"expected\": [true, 110, 4, 4, \"floor\", [110, 20], true], \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":45.158,"exit_code":0,"observations":[{"actual":[true,110,5,5,"floor",[110,20],true],"check":"fixture 1","expected":[true,110,5,5,"floor",[110,20],true],"passed":true},{"actual":[true,120,0,0,"wall",[120,20],false],"check":"fixture 2","expected":[true,120,0,0,"wall",[120,20],false],"passed":true},{"actual":[true,105,0,5,"wall",[105,20],true],"check":"fixture 3","expected":[true,105,0,5,"wall",[105,20],true],"passed":true},{"actual":[true,90,0,0,"wall",[90,20],false],"check":"fixture 4","expected":[true,90,0,0,"wall",[90,20],false],"passed":true},{"actual":[true,100,0,0,"wall",[100,10],false],"check":"fixture 5","expected":[true,100,0,0,"wall",[100,10],false],"passed":true},{"actual":[false,101,0,0,"wall",[100,10],false],"check":"fixture 6","expected":[false,101,0,0,"wall",[100,10],false],"passed":true},{"actual":[true,110,0,0,"wall",[110,20],false],"check":"fixture 7","expected":[true,110,0,0,"wall",[110,20],false],"passed":true},{"actual":[true,110,20,20,"floor",[110,20],true],"check":"fixture 8","expected":[true,110,20,20,"floor",[110,20],true],"passed":true},{"actual":[true,120,15,15,"floor",[120,30],true],"check":"fixture 9","expected":[true,120,15,15,"floor",[120,30],true],"passed":true},{"actual":[true,120,0,0,"wall",[120,10],false],"check":"fixture 10","expected":[true,120,0,0,"wall",[120,10],false],"passed":true},{"actual":[true,110,4,4,"floor",[110,20],true],"check":"variant capture","expected":[true,110,4,4,"floor",[110,20],true],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fixture 1\", \"actual\": [true, 110, 5, 5, \"floor\", [110, 20], true], \"expected\": [true, 110, 5, 5, \"floor\", [110, 20], true], \"passed\": true}, {\"check\": \"fixture 2\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 20], false], \"passed\": true}, {\"check\": \"fixture 3\", \"actual\": [true, 105, 0, 5, \"wall\", [105, 20], true], \"expected\": [true, 105, 0, 5, \"wall\", [105, 20], true], \"passed\": true}, {\"check\": \"fixture 4\", \"actual\": [true, 90, 0, 0, \"wall\", [90, 20], false], \"expected\": [true, 90, 0, 0, \"wall\", [90, 20], false], \"passed\": true}, {\"check\": \"fixture 5\", \"actual\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"expected\": [true, 100, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 6\", \"actual\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"expected\": [false, 101, 0, 0, \"wall\", [100, 10], false], \"passed\": true}, {\"check\": \"fixture 7\", \"actual\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"expected\": [true, 110, 0, 0, \"wall\", [110, 20], false], \"passed\": true}, {\"check\": \"fixture 8\", \"actual\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"expected\": [true, 110, 20, 20, \"floor\", [110, 20], true], \"passed\": true}, {\"check\": \"fixture 9\", \"actual\": [true, 120, 15, 15, \"floor\", [120, 30], true], \"expected\": [true, 120, 15, 15, \"floor\", [120, 30], true], \"passed\": true}, {\"check\": \"fixture 10\", \"actual\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"expected\": [true, 120, 0, 0, \"wall\", [120, 10], false], \"passed\": true}, {\"check\": \"variant capture\", \"actual\": [true, 110, 4, 4, \"floor\", [110, 20], true], \"expected\": [true, 110, 4, 4, \"floor\", [110, 20], true], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}