{"abstract":"In files with out-of-order cues the extension is limited by the wrong neighbour.","category":"Subtitle cue timing","checks":9,"contract":"Cues [start,end] may be unsorted; the neighbour of a cue is the next cue in (start, input index) order. A cue shorter than min_dur has its end extended to start+min_dur, limited to neighbour_start - min_gap; an end is never shortened. Output keeps input order.","contract_signature":"cues, min_dur, min_gap","evaluation_group":"w2-subtitle-cue-timing-min-duration","failed_approach":"Using input order assumes the file is already sorted, which the contract does not guarantee.","family":"w2-subtitle-cue-timing-min-duration-neighbour-ordering","id":"FA-78006","implementations":{"attempt":{"sha256":"e04d853d822847f4eb422f6b4debf10854a6c6a061b35f60e24311f58ee6eab0","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(cues, min_dur, min_gap):\n    out=[list(c) for c in cues]\n    order=list(range(len(out)))\n    for pos,i in enumerate(order):\n        c=out[i]\n        if c[1]-c[0]>=min_dur:\n            continue\n        target=c[0]+min_dur\n        if pos+1<len(order):\n            target=min(target,out[order[pos+1]][0]-min_gap)\n        c[1]=max(c[1],target)\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: neighbour ordering', [[[1000, 1960], [2000, 2300], [3000, 3999], [3000, 3001]], 1000, 40], [[1000, 1960], [2000, 2960], [3000, 3999], [3000, 4000]]), ('regression variant: neighbour ordering', [[[0, 2000], [200, 500]], 700, 80], [[0, 2000], [200, 900]]), ('partial repair probe: neighbour ordering', [[[2000, 2001], [800, 1100]], 1000, 80], [[2000, 3000], [800, 1800]]), ('partial repair variant: neighbour ordering', [[[500, 501], [200, 1160], [0, 1], [500, 1460]], 1000, 40], [[500, 501], [200, 1160], [0, 160], [500, 1500]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('normal control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[0, 1], [200, 900], [2000, 4000]], 700, 0], [[0, 200], [200, 900], [2000, 4000]]), ('normal control', [[[1500, 2700], [1500, 2700]], 1200, 0], [[1500, 2700], [1500, 2700]])], [('regression: neighbour ordering', [[[200, 500], [500, 800], [1500, 3500], [1500, 2699], [2000, 2001]], 1200, 40], [[200, 500], [500, 1460], [1500, 3500], [1500, 2699], [2000, 3200]]), ('regression variant: neighbour ordering', [[[800, 2800], [800, 900], [1500, 1501], [1000, 1700], [3000, 3300]], 700, 0], [[800, 2800], [800, 1000], [1500, 2200], [1000, 1700], [3000, 3700]]), ('partial repair probe: neighbour ordering', [[[0, 1001], [1500, 2500], [3000, 3999], [800, 2800], [0, 1]], 1000, 0], [[0, 1001], [1500, 2500], [3000, 4000], [800, 2800], [0, 800]]), ('partial repair variant: neighbour ordering', [[[200, 900], [0, 699], [800, 2800]], 700, 0], [[200, 900], [0, 699], [800, 2800]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[0, 700], [1000, 1001], [2000, 2699]], 700, 80], [[0, 700], [1000, 1700], [2000, 2700]]), ('normal control', [[[2000, 2100], [3000, 3001]], 700, 0], [[2000, 2700], [3000, 3700]]), ('normal control', [[[200, 1201], [2000, 3001], [1000, 2000], [800, 1800]], 1000, 0], [[200, 1201], [2000, 3001], [1000, 2000], [800, 1800]])], [('regression: neighbour ordering', [[[0, 1001], [1500, 2500], [3000, 3999], [800, 2800], [0, 1]], 1000, 0], [[0, 1001], [1500, 2500], [3000, 4000], [800, 2800], [0, 800]]), ('regression variant: neighbour ordering', [[[3000, 3100], [500, 2500], [2000, 2700], [1131, 1831], [0, 100]], 700, 0], [[3000, 3700], [500, 2500], [2000, 2700], [1131, 1831], [0, 500]]), ('partial repair probe: neighbour ordering', [[[479, 2479], [2000, 2300], [1000, 2120], [800, 2001]], 1200, 80], [[479, 2479], [2000, 3200], [1000, 2120], [800, 2001]]), ('partial repair variant: neighbour ordering', [[[500, 1701], [200, 201], [1000, 1001]], 1200, 0], [[500, 1701], [200, 500], [1000, 2200]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('normal control', [[[500, 501]], 1200, 40], [[500, 1700]]), ('normal control', [[[500, 1200], [1000, 1699]], 700, 0], [[500, 1200], [1000, 1700]]), ('normal control', [[[1500, 3500]], 700, 0], [[1500, 3500]])], [('regression: neighbour ordering', [[[500, 800], [500, 2500], [800, 1799], [1000, 1001], [1000, 3000]], 1000, 40], [[500, 800], [500, 2500], [800, 1799], [1000, 1001], [1000, 3000]]), ('regression variant: neighbour ordering', [[[0, 2000], [200, 1160], [500, 1499], [1186, 1187], [2429, 3430]], 1000, 40], [[0, 2000], [200, 1160], [500, 1499], [1186, 2186], [2429, 3430]]), ('partial repair probe: neighbour ordering', [[[2000, 2999], [500, 1501]], 1000, 80], [[2000, 3000], [500, 1501]]), ('partial repair variant: neighbour ordering', [[[1000, 2000], [0, 1000], [3000, 3999], [2000, 2300], [500, 1500]], 1000, 0], [[1000, 2000], [0, 1000], [3000, 4000], [2000, 3000], [500, 1500]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('normal control', [[[1500, 1600], [1500, 1600], [2000, 3200], [3000, 5000]], 1200, 0], [[1500, 1600], [1500, 2000], [2000, 3200], [3000, 5000]]), ('normal control', [[[1000, 1701], [1500, 2200]], 700, 80], [[1000, 1701], [1500, 2200]]), ('normal control', [[[200, 300], [800, 801]], 1000, 80], [[200, 720], [800, 1800]])], [('regression: neighbour ordering', [[[479, 2479], [2000, 2300], [1000, 2120], [800, 2001]], 1200, 80], [[479, 2479], [2000, 3200], [1000, 2120], [800, 2001]]), ('regression variant: neighbour ordering', [[[500, 2500], [500, 1120], [1000, 1699], [2000, 2701], [2766, 3465]], 700, 80], [[500, 2500], [500, 1120], [1000, 1700], [2000, 2701], [2766, 3466]]), ('partial repair probe: neighbour ordering', [[[800, 2800], [800, 900], [1500, 1501], [1000, 1700], [3000, 3300]], 700, 0], [[800, 2800], [800, 1000], [1500, 2200], [1000, 1700], [3000, 3700]]), ('partial repair variant: neighbour ordering', [[[1000, 3000], [3955, 4055], [208, 1207], [1500, 2420]], 1000, 80], [[1000, 3000], [3955, 4955], [208, 1207], [1500, 2500]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[209, 1409], [800, 2001], [1500, 2620]], 1200, 80], [[209, 1409], [800, 2001], [1500, 2700]]), ('normal control', [[[0, 701], [800, 1460], [800, 2800], [4594, 4894]], 700, 40], [[0, 701], [800, 1460], [800, 2800], [4594, 5294]]), ('normal control', [[[200, 500], [1394, 2593], [3000, 3300]], 1200, 80], [[200, 1314], [1394, 2594], [3000, 4200]])]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\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":"95826cb2917c4f91c0e6c14e4705155e00b94a260462be1240286fabd1bd1c11","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(cues, min_dur, min_gap):\n    out=[list(c) for c in cues]\n    order=sorted(range(len(out)),key=lambda k:(out[k][1],k))\n    for pos,i in enumerate(order):\n        c=out[i]\n        if c[1]-c[0]>=min_dur:\n            continue\n        target=c[0]+min_dur\n        if pos+1<len(order):\n            target=min(target,out[order[pos+1]][0]-min_gap)\n        c[1]=max(c[1],target)\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: neighbour ordering', [[[1000, 1960], [2000, 2300], [3000, 3999], [3000, 3001]], 1000, 40], [[1000, 1960], [2000, 2960], [3000, 3999], [3000, 4000]]), ('regression variant: neighbour ordering', [[[0, 2000], [200, 500]], 700, 80], [[0, 2000], [200, 900]]), ('partial repair probe: neighbour ordering', [[[2000, 2001], [800, 1100]], 1000, 80], [[2000, 3000], [800, 1800]]), ('partial repair variant: neighbour ordering', [[[500, 501], [200, 1160], [0, 1], [500, 1460]], 1000, 40], [[500, 501], [200, 1160], [0, 160], [500, 1500]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('normal control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[0, 1], [200, 900], [2000, 4000]], 700, 0], [[0, 200], [200, 900], [2000, 4000]]), ('normal control', [[[1500, 2700], [1500, 2700]], 1200, 0], [[1500, 2700], [1500, 2700]])], [('regression: neighbour ordering', [[[200, 500], [500, 800], [1500, 3500], [1500, 2699], [2000, 2001]], 1200, 40], [[200, 500], [500, 1460], [1500, 3500], [1500, 2699], [2000, 3200]]), ('regression variant: neighbour ordering', [[[800, 2800], [800, 900], [1500, 1501], [1000, 1700], [3000, 3300]], 700, 0], [[800, 2800], [800, 1000], [1500, 2200], [1000, 1700], [3000, 3700]]), ('partial repair probe: neighbour ordering', [[[0, 1001], [1500, 2500], [3000, 3999], [800, 2800], [0, 1]], 1000, 0], [[0, 1001], [1500, 2500], [3000, 4000], [800, 2800], [0, 800]]), ('partial repair variant: neighbour ordering', [[[200, 900], [0, 699], [800, 2800]], 700, 0], [[200, 900], [0, 699], [800, 2800]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[0, 700], [1000, 1001], [2000, 2699]], 700, 80], [[0, 700], [1000, 1700], [2000, 2700]]), ('normal control', [[[2000, 2100], [3000, 3001]], 700, 0], [[2000, 2700], [3000, 3700]]), ('normal control', [[[200, 1201], [2000, 3001], [1000, 2000], [800, 1800]], 1000, 0], [[200, 1201], [2000, 3001], [1000, 2000], [800, 1800]])], [('regression: neighbour ordering', [[[0, 1001], [1500, 2500], [3000, 3999], [800, 2800], [0, 1]], 1000, 0], [[0, 1001], [1500, 2500], [3000, 4000], [800, 2800], [0, 800]]), ('regression variant: neighbour ordering', [[[3000, 3100], [500, 2500], [2000, 2700], [1131, 1831], [0, 100]], 700, 0], [[3000, 3700], [500, 2500], [2000, 2700], [1131, 1831], [0, 500]]), ('partial repair probe: neighbour ordering', [[[479, 2479], [2000, 2300], [1000, 2120], [800, 2001]], 1200, 80], [[479, 2479], [2000, 3200], [1000, 2120], [800, 2001]]), ('partial repair variant: neighbour ordering', [[[500, 1701], [200, 201], [1000, 1001]], 1200, 0], [[500, 1701], [200, 500], [1000, 2200]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('normal control', [[[500, 501]], 1200, 40], [[500, 1700]]), ('normal control', [[[500, 1200], [1000, 1699]], 700, 0], [[500, 1200], [1000, 1700]]), ('normal control', [[[1500, 3500]], 700, 0], [[1500, 3500]])], [('regression: neighbour ordering', [[[500, 800], [500, 2500], [800, 1799], [1000, 1001], [1000, 3000]], 1000, 40], [[500, 800], [500, 2500], [800, 1799], [1000, 1001], [1000, 3000]]), ('regression variant: neighbour ordering', [[[0, 2000], [200, 1160], [500, 1499], [1186, 1187], [2429, 3430]], 1000, 40], [[0, 2000], [200, 1160], [500, 1499], [1186, 2186], [2429, 3430]]), ('partial repair probe: neighbour ordering', [[[2000, 2999], [500, 1501]], 1000, 80], [[2000, 3000], [500, 1501]]), ('partial repair variant: neighbour ordering', [[[1000, 2000], [0, 1000], [3000, 3999], [2000, 2300], [500, 1500]], 1000, 0], [[1000, 2000], [0, 1000], [3000, 4000], [2000, 3000], [500, 1500]]), ('boundary control', [[[0, 300], [2000, 3000]], 1000, 80], [[0, 1000], [2000, 3000]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('normal control', [[[1500, 1600], [1500, 1600], [2000, 3200], [3000, 5000]], 1200, 0], [[1500, 1600], [1500, 2000], [2000, 3200], [3000, 5000]]), ('normal control', [[[1000, 1701], [1500, 2200]], 700, 80], [[1000, 1701], [1500, 2200]]), ('normal control', [[[200, 300], [800, 801]], 1000, 80], [[200, 720], [800, 1800]])], [('regression: neighbour ordering', [[[479, 2479], [2000, 2300], [1000, 2120], [800, 2001]], 1200, 80], [[479, 2479], [2000, 3200], [1000, 2120], [800, 2001]]), ('regression variant: neighbour ordering', [[[500, 2500], [500, 1120], [1000, 1699], [2000, 2701], [2766, 3465]], 700, 80], [[500, 2500], [500, 1120], [1000, 1700], [2000, 2701], [2766, 3466]]), ('partial repair probe: neighbour ordering', [[[800, 2800], [800, 900], [1500, 1501], [1000, 1700], [3000, 3300]], 700, 0], [[800, 2800], [800, 1000], [1500, 2200], [1000, 1700], [3000, 3700]]), ('partial repair variant: neighbour ordering', [[[1000, 3000], [3955, 4055], [208, 1207], [1500, 2420]], 1000, 80], [[1000, 3000], [3955, 4955], [208, 1207], [1500, 2500]]), ('boundary control', [[[0, 300], [500, 3000]], 1000, 80], [[0, 420], [500, 3000]]), ('boundary control', [[[0, 1000]], 1000, 0], [[0, 1000]]), ('normal control', [[[209, 1409], [800, 2001], [1500, 2620]], 1200, 80], [[209, 1409], [800, 2001], [1500, 2700]]), ('normal control', [[[0, 701], [800, 1460], [800, 2800], [4594, 4894]], 700, 40], [[0, 701], [800, 1460], [800, 2800], [4594, 5294]]), ('normal control', [[[200, 500], [1394, 2593], [3000, 3300]], 1200, 80], [[200, 1314], [1394, 2594], [3000, 4200]])]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\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":"A deterministic bounded teaching model with a stipulated toy contract; it does not claim conformance to any subtitle standard. 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":"w2-subtitle-cue-timing-min-duration-neighbour-ordering","generated_at":"2026-09-29T14:49:31.300989+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Subtitle timing defects shift, hide or overlap captions that viewers depend on for comprehension and accessibility.","root_cause":"Neighbours are ordered by end time instead of start time.","sha256":"e81467c429ccba6eae6420cc9380c77be57ed15dfc58005e360f1e9c7dc7de11","title":"Minimum cue duration extension: neighbour ordering · 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":41.075,"exit_code":1,"observations":[{"actual":[[1000,1960],[2000,2960],[3000,3999],[3000,4000]],"check":"regression: neighbour ordering","expected":[[1000,1960],[2000,2960],[3000,3999],[3000,4000]],"passed":true},{"actual":[[0,2000],[200,900]],"check":"regression variant: neighbour ordering","expected":[[0,2000],[200,900]],"passed":true},{"actual":[[2000,2001],[800,1800]],"check":"partial repair probe: neighbour ordering","expected":[[2000,3000],[800,1800]],"passed":false},{"actual":[[500,501],[200,1160],[0,460],[500,1500]],"check":"partial repair variant: neighbour ordering","expected":[[500,501],[200,1160],[0,160],[500,1500]],"passed":false},{"actual":[[0,1000],[2000,3000]],"check":"boundary control","expected":[[0,1000],[2000,3000]],"passed":true},{"actual":[[0,420],[500,3000]],"check":"boundary control","expected":[[0,420],[500,3000]],"passed":true},{"actual":[[0,1000]],"check":"normal control","expected":[[0,1000]],"passed":true},{"actual":[[0,200],[200,900],[2000,4000]],"check":"normal control","expected":[[0,200],[200,900],[2000,4000]],"passed":true},{"actual":[[1500,2700],[1500,2700]],"check":"normal control","expected":[[1500,2700],[1500,2700]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: neighbour ordering\", \"actual\": [[1000, 1960], [2000, 2960], [3000, 3999], [3000, 4000]], \"expected\": [[1000, 1960], [2000, 2960], [3000, 3999], [3000, 4000]], \"passed\": true}, {\"check\": \"regression variant: neighbour ordering\", \"actual\": [[0, 2000], [200, 900]], \"expected\": [[0, 2000], [200, 900]], \"passed\": true}, {\"check\": \"partial repair probe: neighbour ordering\", \"actual\": [[2000, 2001], [800, 1800]], \"expected\": [[2000, 3000], [800, 1800]], \"passed\": false}, {\"check\": \"partial repair variant: neighbour ordering\", \"actual\": [[500, 501], [200, 1160], [0, 460], [500, 1500]], \"expected\": [[500, 501], [200, 1160], [0, 160], [500, 1500]], \"passed\": false}, {\"check\": \"boundary control\", \"actual\": [[0, 1000], [2000, 3000]], \"expected\": [[0, 1000], [2000, 3000]], \"passed\": true}, {\"check\": \"boundary control\", \"actual\": [[0, 420], [500, 3000]], \"expected\": [[0, 420], [500, 3000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[0, 1000]], \"expected\": [[0, 1000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[0, 200], [200, 900], [2000, 4000]], \"expected\": [[0, 200], [200, 900], [2000, 4000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[1500, 2700], [1500, 2700]], \"expected\": [[1500, 2700], [1500, 2700]], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.741,"exit_code":1,"observations":[{"actual":[[1000,1960],[2000,2960],[3000,4000],[3000,3001]],"check":"regression: neighbour ordering","expected":[[1000,1960],[2000,2960],[3000,3999],[3000,4000]],"passed":false},{"actual":[[0,2000],[200,500]],"check":"regression variant: neighbour ordering","expected":[[0,2000],[200,900]],"passed":false},{"actual":[[2000,3000],[800,1800]],"check":"partial repair probe: neighbour ordering","expected":[[2000,3000],[800,1800]],"passed":true},{"actual":[[500,501],[200,1160],[0,460],[500,1500]],"check":"partial repair variant: neighbour ordering","expected":[[500,501],[200,1160],[0,160],[500,1500]],"passed":false},{"actual":[[0,1000],[2000,3000]],"check":"boundary control","expected":[[0,1000],[2000,3000]],"passed":true},{"actual":[[0,420],[500,3000]],"check":"boundary control","expected":[[0,420],[500,3000]],"passed":true},{"actual":[[0,1000]],"check":"normal control","expected":[[0,1000]],"passed":true},{"actual":[[0,200],[200,900],[2000,4000]],"check":"normal control","expected":[[0,200],[200,900],[2000,4000]],"passed":true},{"actual":[[1500,2700],[1500,2700]],"check":"normal control","expected":[[1500,2700],[1500,2700]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: neighbour ordering\", \"actual\": [[1000, 1960], [2000, 2960], [3000, 4000], [3000, 3001]], \"expected\": [[1000, 1960], [2000, 2960], [3000, 3999], [3000, 4000]], \"passed\": false}, {\"check\": \"regression variant: neighbour ordering\", \"actual\": [[0, 2000], [200, 500]], \"expected\": [[0, 2000], [200, 900]], \"passed\": false}, {\"check\": \"partial repair probe: neighbour ordering\", \"actual\": [[2000, 3000], [800, 1800]], \"expected\": [[2000, 3000], [800, 1800]], \"passed\": true}, {\"check\": \"partial repair variant: neighbour ordering\", \"actual\": [[500, 501], [200, 1160], [0, 460], [500, 1500]], \"expected\": [[500, 501], [200, 1160], [0, 160], [500, 1500]], \"passed\": false}, {\"check\": \"boundary control\", \"actual\": [[0, 1000], [2000, 3000]], \"expected\": [[0, 1000], [2000, 3000]], \"passed\": true}, {\"check\": \"boundary control\", \"actual\": [[0, 420], [500, 3000]], \"expected\": [[0, 420], [500, 3000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[0, 1000]], \"expected\": [[0, 1000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[0, 200], [200, 900], [2000, 4000]], \"expected\": [[0, 200], [200, 900], [2000, 4000]], \"passed\": true}, {\"check\": \"normal control\", \"actual\": [[1500, 2700], [1500, 2700]], \"expected\": [[1500, 2700], [1500, 2700]], \"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."}}