{"abstract":"Equally near cars are chosen by listing order, or a far car is chosen.","category":"Elevator dispatch scheduling","checks":8,"contract":"The building is split into zones of ceil(floors/zones) floors; each zone base floor is a parking target. Up-peak adds an extra lobby target first (lobby gets two cars); down-peak orders the bases from the top down; otherwise bases ascend. Each target in order takes the nearest free car (ties to the lowest car id); leftover targets stay empty.","contract_signature":"x","evaluation_group":"w2-elevator_dispatch_scheduling-idle-car-parking","failed_approach":"Picking the lowest-positioned car ignores distance to the target.","family":"w2-elevator_dispatch_scheduling-idle-car-parking-nearest-car-tie-break","id":"FA-67491","implementations":{"attempt":{"sha256":"b9c9861c7a85dc2c7aa3f3ee6c7c2b1fccc6476f1ba6ec2e8fa102ca49dfaff4","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    n = x['floors']\n    k = x['zones']\n    size = -(-n // k)\n    bases = [z * size for z in range(k) if z * size < n]\n    if x['period'] == 'up-peak':\n        targets = [0] + bases\n    elif x['period'] == 'down-peak':\n        targets = sorted(bases, reverse=True)\n    else:\n        targets = bases\n    free = dict(x['cars'])\n    plan = {}\n    for t in targets:\n        if not free:\n            break\n        cid = min(free, key=lambda c: (free[c], c))\n        plan[cid] = t\n        del free[cid]\n    return plan\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 11', {'floors': 10, 'zones': 1, 'period': 'up-peak', 'cars': [['C2', 7], ['C5', 9], ['C3', 0], ['C4', 7], ['C1', 7]]}, {'C3': 0, 'C1': 0}), ('control 3', {'floors': 12, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 6], ['C2', 1], ['C5', 2], ['C3', 10], ['C4', 4]]}, {'C1': 6, 'C2': 0}), ('boundary: ten floors in three zones', {'floors': 10, 'zones': 3, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 5], ['C3', 1]]}, {'C3': 0, 'C2': 4, 'C1': 8}), ('control 1', {'floors': 8, 'zones': 3, 'period': 'off-peak', 'cars': [['C2', 3], ['C1', 7], ['C5', 4]]}, {'C2': 0, 'C5': 3, 'C1': 6}), ('control 4', {'floors': 27, 'zones': 2, 'period': 'down-peak', 'cars': [['C3', 14], ['C5', 10]]}, {'C3': 14, 'C5': 0}), ('sampled regression 7', {'floors': 14, 'zones': 3, 'period': 'down-peak', 'cars': [['C5', 13], ['C4', 0], ['C2', 11], ['C3', 5], ['C1', 11]]}, {'C1': 10, 'C3': 5, 'C4': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('control 16', {'floors': 14, 'zones': 4, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 2], ['C3', 12], ['C4', 0], ['C5', 3]]}, {'C4': 0, 'C5': 4, 'C1': 8, 'C3': 12}), ('boundary: up-peak lobby pair', {'floors': 12, 'zones': 2, 'period': 'up-peak', 'cars': [['C1', 3], ['C2', 8], ['C3', 11]]}, {'C1': 0, 'C2': 0, 'C3': 6}), ('boundary: fewer cars than targets', {'floors': 20, 'zones': 4, 'period': 'up-peak', 'cars': [['C2', 7]]}, {'C2': 0}), ('control 12', {'floors': 14, 'zones': 2, 'period': 'off-peak', 'cars': [['C3', 9], ['C5', 5]]}, {'C5': 0, 'C3': 7}), ('control 15', {'floors': 22, 'zones': 1, 'period': 'off-peak', 'cars': [['C5', 11]]}, {'C5': 0}), ('control 18', {'floors': 10, 'zones': 2, 'period': 'down-peak', 'cars': [['C4', 7], ['C2', 2], ['C1', 0], ['C5', 0], ['C3', 5]]}, {'C3': 5, 'C1': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 44', {'floors': 9, 'zones': 2, 'period': 'up-peak', 'cars': [['C3', 4], ['C2', 2], ['C5', 8], ['C1', 4]]}, {'C2': 0, 'C1': 0, 'C3': 5}), ('control 26', {'floors': 9, 'zones': 2, 'period': 'down-peak', 'cars': [['C2', 1], ['C4', 8], ['C1', 0], ['C5', 8], ['C3', 6]]}, {'C3': 5, 'C1': 0}), ('boundary: fewer cars than targets', {'floors': 20, 'zones': 4, 'period': 'up-peak', 'cars': [['C2', 7]]}, {'C2': 0}), ('control 23', {'floors': 8, 'zones': 4, 'period': 'down-peak', 'cars': [['C3', 5], ['C4', 7]]}, {'C3': 6, 'C4': 4}), ('control 29', {'floors': 30, 'zones': 3, 'period': 'down-peak', 'cars': [['C3', 28], ['C5', 0], ['C2', 17], ['C4', 12], ['C1', 29]]}, {'C2': 20, 'C4': 10, 'C5': 0}), ('control 32', {'floors': 12, 'zones': 1, 'period': 'down-peak', 'cars': [['C4', 3], ['C5', 0], ['C2', 11]]}, {'C5': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 14', {'floors': 8, 'zones': 4, 'period': 'off-peak', 'cars': [['C2', 1], ['C3', 4], ['C5', 1], ['C1', 1]]}, {'C1': 0, 'C2': 2, 'C3': 4, 'C5': 6}), ('control 39', {'floors': 25, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 11], ['C5', 15]]}, {'C5': 21, 'C1': 14}), ('boundary: ten floors in three zones', {'floors': 10, 'zones': 3, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 5], ['C3', 1]]}, {'C3': 0, 'C2': 4, 'C1': 8}), ('control 34', {'floors': 17, 'zones': 2, 'period': 'off-peak', 'cars': [['C5', 2], ['C2', 7], ['C1', 0]]}, {'C1': 0, 'C2': 9}), ('control 37', {'floors': 9, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 3], ['C5', 8], ['C4', 7]]}, {'C1': 5, 'C4': 0}), ('control 40', {'floors': 24, 'zones': 1, 'period': 'off-peak', 'cars': [['C4', 6]]}, {'C4': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 2', {'floors': 24, 'zones': 3, 'period': 'down-peak', 'cars': [['C5', 23], ['C4', 9]]}, {'C4': 16, 'C5': 8}), ('control 57', {'floors': 13, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 11], ['C2', 8], ['C4', 5]]}, {'C2': 7, 'C4': 0}), ('boundary: up-peak lobby pair', {'floors': 12, 'zones': 2, 'period': 'up-peak', 'cars': [['C1', 3], ['C2', 8], ['C3', 11]]}, {'C1': 0, 'C2': 0, 'C3': 6}), ('control 45', {'floors': 9, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 6], ['C4', 1], ['C5', 0], ['C2', 1], ['C1', 7]]}, {'C5': 0}), ('control 48', {'floors': 16, 'zones': 3, 'period': 'up-peak', 'cars': [['C4', 9], ['C3', 7], ['C2', 14], ['C1', 7]]}, {'C1': 0, 'C3': 0, 'C4': 6, 'C2': 12}), ('control 51', {'floors': 18, 'zones': 4, 'period': 'off-peak', 'cars': [['C5', 11]]}, {'C5': 0})]]\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":"3d7df0998c3e430355ec87bf9683c71631fead224b72ff39d7bfcc5704084e8c","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    n = x['floors']\n    k = x['zones']\n    size = -(-n // k)\n    bases = [z * size for z in range(k) if z * size < n]\n    if x['period'] == 'up-peak':\n        targets = [0] + bases\n    elif x['period'] == 'down-peak':\n        targets = sorted(bases, reverse=True)\n    else:\n        targets = bases\n    free = dict(x['cars'])\n    plan = {}\n    for t in targets:\n        if not free:\n            break\n        cid = min(free, key=lambda c: abs(free[c] - t))\n        plan[cid] = t\n        del free[cid]\n    return plan\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 11', {'floors': 10, 'zones': 1, 'period': 'up-peak', 'cars': [['C2', 7], ['C5', 9], ['C3', 0], ['C4', 7], ['C1', 7]]}, {'C3': 0, 'C1': 0}), ('control 3', {'floors': 12, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 6], ['C2', 1], ['C5', 2], ['C3', 10], ['C4', 4]]}, {'C1': 6, 'C2': 0}), ('boundary: ten floors in three zones', {'floors': 10, 'zones': 3, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 5], ['C3', 1]]}, {'C3': 0, 'C2': 4, 'C1': 8}), ('control 1', {'floors': 8, 'zones': 3, 'period': 'off-peak', 'cars': [['C2', 3], ['C1', 7], ['C5', 4]]}, {'C2': 0, 'C5': 3, 'C1': 6}), ('control 4', {'floors': 27, 'zones': 2, 'period': 'down-peak', 'cars': [['C3', 14], ['C5', 10]]}, {'C3': 14, 'C5': 0}), ('sampled regression 7', {'floors': 14, 'zones': 3, 'period': 'down-peak', 'cars': [['C5', 13], ['C4', 0], ['C2', 11], ['C3', 5], ['C1', 11]]}, {'C1': 10, 'C3': 5, 'C4': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('control 16', {'floors': 14, 'zones': 4, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 2], ['C3', 12], ['C4', 0], ['C5', 3]]}, {'C4': 0, 'C5': 4, 'C1': 8, 'C3': 12}), ('boundary: up-peak lobby pair', {'floors': 12, 'zones': 2, 'period': 'up-peak', 'cars': [['C1', 3], ['C2', 8], ['C3', 11]]}, {'C1': 0, 'C2': 0, 'C3': 6}), ('boundary: fewer cars than targets', {'floors': 20, 'zones': 4, 'period': 'up-peak', 'cars': [['C2', 7]]}, {'C2': 0}), ('control 12', {'floors': 14, 'zones': 2, 'period': 'off-peak', 'cars': [['C3', 9], ['C5', 5]]}, {'C5': 0, 'C3': 7}), ('control 15', {'floors': 22, 'zones': 1, 'period': 'off-peak', 'cars': [['C5', 11]]}, {'C5': 0}), ('control 18', {'floors': 10, 'zones': 2, 'period': 'down-peak', 'cars': [['C4', 7], ['C2', 2], ['C1', 0], ['C5', 0], ['C3', 5]]}, {'C3': 5, 'C1': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 44', {'floors': 9, 'zones': 2, 'period': 'up-peak', 'cars': [['C3', 4], ['C2', 2], ['C5', 8], ['C1', 4]]}, {'C2': 0, 'C1': 0, 'C3': 5}), ('control 26', {'floors': 9, 'zones': 2, 'period': 'down-peak', 'cars': [['C2', 1], ['C4', 8], ['C1', 0], ['C5', 8], ['C3', 6]]}, {'C3': 5, 'C1': 0}), ('boundary: fewer cars than targets', {'floors': 20, 'zones': 4, 'period': 'up-peak', 'cars': [['C2', 7]]}, {'C2': 0}), ('control 23', {'floors': 8, 'zones': 4, 'period': 'down-peak', 'cars': [['C3', 5], ['C4', 7]]}, {'C3': 6, 'C4': 4}), ('control 29', {'floors': 30, 'zones': 3, 'period': 'down-peak', 'cars': [['C3', 28], ['C5', 0], ['C2', 17], ['C4', 12], ['C1', 29]]}, {'C2': 20, 'C4': 10, 'C5': 0}), ('control 32', {'floors': 12, 'zones': 1, 'period': 'down-peak', 'cars': [['C4', 3], ['C5', 0], ['C2', 11]]}, {'C5': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 14', {'floors': 8, 'zones': 4, 'period': 'off-peak', 'cars': [['C2', 1], ['C3', 4], ['C5', 1], ['C1', 1]]}, {'C1': 0, 'C2': 2, 'C3': 4, 'C5': 6}), ('control 39', {'floors': 25, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 11], ['C5', 15]]}, {'C5': 21, 'C1': 14}), ('boundary: ten floors in three zones', {'floors': 10, 'zones': 3, 'period': 'off-peak', 'cars': [['C1', 9], ['C2', 5], ['C3', 1]]}, {'C3': 0, 'C2': 4, 'C1': 8}), ('control 34', {'floors': 17, 'zones': 2, 'period': 'off-peak', 'cars': [['C5', 2], ['C2', 7], ['C1', 0]]}, {'C1': 0, 'C2': 9}), ('control 37', {'floors': 9, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 3], ['C5', 8], ['C4', 7]]}, {'C1': 5, 'C4': 0}), ('control 40', {'floors': 24, 'zones': 1, 'period': 'off-peak', 'cars': [['C4', 6]]}, {'C4': 0})], [('regression: equidistant cars listed out of order', {'floors': 10, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 2], ['C1', 2]]}, {'C1': 0}), ('boundary: down-peak top first', {'floors': 20, 'zones': 4, 'period': 'down-peak', 'cars': [['C1', 16], ['C2', 13], ['C3', 2]]}, {'C1': 15, 'C2': 10, 'C3': 5}), ('sampled regression 2', {'floors': 24, 'zones': 3, 'period': 'down-peak', 'cars': [['C5', 23], ['C4', 9]]}, {'C4': 16, 'C5': 8}), ('control 57', {'floors': 13, 'zones': 2, 'period': 'down-peak', 'cars': [['C1', 11], ['C2', 8], ['C4', 5]]}, {'C2': 7, 'C4': 0}), ('boundary: up-peak lobby pair', {'floors': 12, 'zones': 2, 'period': 'up-peak', 'cars': [['C1', 3], ['C2', 8], ['C3', 11]]}, {'C1': 0, 'C2': 0, 'C3': 6}), ('control 45', {'floors': 9, 'zones': 1, 'period': 'off-peak', 'cars': [['C3', 6], ['C4', 1], ['C5', 0], ['C2', 1], ['C1', 7]]}, {'C5': 0}), ('control 48', {'floors': 16, 'zones': 3, 'period': 'up-peak', 'cars': [['C4', 9], ['C3', 7], ['C2', 14], ['C1', 7]]}, {'C1': 0, 'C3': 0, 'C4': 6, 'C2': 12}), ('control 51', {'floors': 18, 'zones': 4, 'period': 'off-peak', 'cars': [['C5', 11]]}, {'C5': 0})]]\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":"Stipulated toy lift-control contract for a bounded teaching model; it makes no claim of conformance to any lift code or vendor dispatcher and omits real safety cases. 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-elevator_dispatch_scheduling-idle-car-parking-nearest-car-tie-break","generated_at":"2026-09-29T14:47:53.294660+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Lift group controllers make these decisions many times per minute; a wrong answer strands passengers, wastes trips or overrides a safety rule.","root_cause":"The tie falls to dictionary insertion order.","sha256":"5751763d1bee305e23eb922152eee900cc2babbeec3b02803119d9e52a44ac6d","title":"Idle car parking by zone: nearest car tie-break · 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":41.475,"exit_code":1,"observations":[{"actual":{"C1":0},"check":"regression: equidistant cars listed out of order","expected":{"C1":0},"passed":true},{"actual":{"C1":5,"C2":10,"C3":15},"check":"boundary: down-peak top first","expected":{"C1":15,"C2":10,"C3":5},"passed":false},{"actual":{"C1":0,"C3":0},"check":"sampled regression 11","expected":{"C1":0,"C3":0},"passed":true},{"actual":{"C2":6,"C5":0},"check":"control 3","expected":{"C1":6,"C2":0},"passed":false},{"actual":{"C1":8,"C2":4,"C3":0},"check":"boundary: ten floors in three zones","expected":{"C1":8,"C2":4,"C3":0},"passed":true},{"actual":{"C1":6,"C2":0,"C5":3},"check":"control 1","expected":{"C1":6,"C2":0,"C5":3},"passed":true},{"actual":{"C3":0,"C5":14},"check":"control 4","expected":{"C3":14,"C5":0},"passed":false},{"actual":{"C1":0,"C3":5,"C4":10},"check":"sampled regression 7","expected":{"C1":10,"C3":5,"C4":0},"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: equidistant cars listed out of order\", \"actual\": {\"C1\": 0}, \"expected\": {\"C1\": 0}, \"passed\": true}, {\"check\": \"boundary: down-peak top first\", \"actual\": {\"C3\": 15, \"C2\": 10, \"C1\": 5}, \"expected\": {\"C1\": 15, \"C2\": 10, \"C3\": 5}, \"passed\": false}, {\"check\": \"sampled regression 11\", \"actual\": {\"C3\": 0, \"C1\": 0}, \"expected\": {\"C3\": 0, \"C1\": 0}, \"passed\": true}, {\"check\": \"control 3\", \"actual\": {\"C2\": 6, \"C5\": 0}, \"expected\": {\"C1\": 6, \"C2\": 0}, \"passed\": false}, {\"check\": \"boundary: ten floors in three zones\", \"actual\": {\"C3\": 0, \"C2\": 4, \"C1\": 8}, \"expected\": {\"C3\": 0, \"C2\": 4, \"C1\": 8}, \"passed\": true}, {\"check\": \"control 1\", \"actual\": {\"C2\": 0, \"C5\": 3, \"C1\": 6}, \"expected\": {\"C2\": 0, \"C5\": 3, \"C1\": 6}, \"passed\": true}, {\"check\": \"control 4\", \"actual\": {\"C5\": 14, \"C3\": 0}, \"expected\": {\"C3\": 14, \"C5\": 0}, \"passed\": false}, {\"check\": \"sampled regression 7\", \"actual\": {\"C4\": 10, \"C3\": 5, \"C1\": 0}, \"expected\": {\"C1\": 10, \"C3\": 5, \"C4\": 0}, \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.046,"exit_code":1,"observations":[{"actual":{"C3":0},"check":"regression: equidistant cars listed out of order","expected":{"C1":0},"passed":false},{"actual":{"C1":15,"C2":10,"C3":5},"check":"boundary: down-peak top first","expected":{"C1":15,"C2":10,"C3":5},"passed":true},{"actual":{"C2":0,"C3":0},"check":"sampled regression 11","expected":{"C1":0,"C3":0},"passed":false},{"actual":{"C1":6,"C2":0},"check":"control 3","expected":{"C1":6,"C2":0},"passed":true},{"actual":{"C1":8,"C2":4,"C3":0},"check":"boundary: ten floors in three zones","expected":{"C1":8,"C2":4,"C3":0},"passed":true},{"actual":{"C1":6,"C2":0,"C5":3},"check":"control 1","expected":{"C1":6,"C2":0,"C5":3},"passed":true},{"actual":{"C3":14,"C5":0},"check":"control 4","expected":{"C3":14,"C5":0},"passed":true},{"actual":{"C2":10,"C3":5,"C4":0},"check":"sampled regression 7","expected":{"C1":10,"C3":5,"C4":0},"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: equidistant cars listed out of order\", \"actual\": {\"C3\": 0}, \"expected\": {\"C1\": 0}, \"passed\": false}, {\"check\": \"boundary: down-peak top first\", \"actual\": {\"C1\": 15, \"C2\": 10, \"C3\": 5}, \"expected\": {\"C1\": 15, \"C2\": 10, \"C3\": 5}, \"passed\": true}, {\"check\": \"sampled regression 11\", \"actual\": {\"C3\": 0, \"C2\": 0}, \"expected\": {\"C3\": 0, \"C1\": 0}, \"passed\": false}, {\"check\": \"control 3\", \"actual\": {\"C1\": 6, \"C2\": 0}, \"expected\": {\"C1\": 6, \"C2\": 0}, \"passed\": true}, {\"check\": \"boundary: ten floors in three zones\", \"actual\": {\"C3\": 0, \"C2\": 4, \"C1\": 8}, \"expected\": {\"C3\": 0, \"C2\": 4, \"C1\": 8}, \"passed\": true}, {\"check\": \"control 1\", \"actual\": {\"C2\": 0, \"C5\": 3, \"C1\": 6}, \"expected\": {\"C2\": 0, \"C5\": 3, \"C1\": 6}, \"passed\": true}, {\"check\": \"control 4\", \"actual\": {\"C3\": 14, \"C5\": 0}, \"expected\": {\"C3\": 14, \"C5\": 0}, \"passed\": true}, {\"check\": \"sampled regression 7\", \"actual\": {\"C2\": 10, \"C3\": 5, \"C4\": 0}, \"expected\": {\"C1\": 10, \"C3\": 5, \"C4\": 0}, \"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."}}