{"abstract":"The mean wait is one second high.","category":"Elevator dispatch scheduling","checks":8,"contract":"Each hall call has a registration time and an answer time (None if still unanswered at end_s). Waits are answer - registration clamped at zero (clock skew); unanswered calls count with the censored wait end_s - registration. Report the integer mean (floor), per-mille of waits over 60 s (floor), the maximum and the count; all zeros when there are no calls.","evaluation_group":"w2-elevator_dispatch_scheduling-waiting-time-statistics","failed_approach":"Ceiling division always rounds a fractional mean up.","family":"w2-elevator_dispatch_scheduling-waiting-time-statistics-mean-rounding","id":"FA-67531","implementations":{"attempt":{"sha256":"6ae0f95572fd3e6c43a23937caf187350a3285d279347685229c57c1cf91f08f","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    waits = []\n    for reg, ans in x['calls']:\n        if ans is None:\n            waits.append(x['end_s'] - reg)\n        else:\n            waits.append(max(0, ans - reg))\n    if not waits:\n        return {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}\n    longs = sum(1 for w in waits if w > 60)\n    return {'avg': -(-sum(waits) // len(waits)), 'long_permille': longs * 1000 // len(waits), 'max': max(waits), 'count': len(waits)}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 1', {'end_s': 600, 'calls': [[93, 138], [499, 519], [546, None], [485, None], [376, 526], [329, 419], [42, None], [303, None]]}, {'avg': 166, 'long_permille': 625, 'max': 558, 'count': 8}), ('control 4', {'end_s': 600, 'calls': [[15, None], [80, 100], [304, 324], [560, 557], [73, 78], [574, None]]}, {'avg': 109, 'long_permille': 166, 'max': 585, 'count': 6}), ('sampled regression 7', {'end_s': 600, 'calls': [[196, 216], [228, 248], [100, None], [381, 471], [370, 415], [56, 76]]}, {'avg': 115, 'long_permille': 333, 'max': 500, 'count': 6})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('control 6', {'end_s': 600, 'calls': [[541, None], [503, 502], [554, None], [543, None], [284, 434]]}, {'avg': 62, 'long_permille': 200, 'max': 150, 'count': 5}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('control 12', {'end_s': 600, 'calls': [[549, None], [34, 94], [153, 243]]}, {'avg': 67, 'long_permille': 333, 'max': 90, 'count': 3}), ('sampled regression 15', {'end_s': 600, 'calls': [[427, 472], [290, 440], [125, None], [18, 79], [88, 178], [156, 306], [7, None], [120, None]]}, {'avg': 255, 'long_permille': 875, 'max': 593, 'count': 8}), ('control 18', {'end_s': 600, 'calls': [[508, 528]]}, {'avg': 20, 'long_permille': 0, 'max': 20, 'count': 1})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('sampled regression 61', {'end_s': 600, 'calls': [[410, 415], [504, 564], [213, 258], [291, None], [359, None], [364, 369], [125, None]]}, {'avg': 162, 'long_permille': 428, 'max': 475, 'count': 7}), ('control 13', {'end_s': 600, 'calls': [[451, 511], [494, 539], [553, None], [26, None], [306, 367], [164, 314], [548, None], [406, 556]]}, {'avg': 142, 'long_permille': 500, 'max': 574, 'count': 8}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 23', {'end_s': 600, 'calls': [[121, 141], [388, None], [577, None]]}, {'avg': 85, 'long_permille': 333, 'max': 212, 'count': 3}), ('control 26', {'end_s': 600, 'calls': [[205, 225], [336, 381]]}, {'avg': 32, 'long_permille': 0, 'max': 45, 'count': 2}), ('sampled regression 29', {'end_s': 600, 'calls': [[26, 31], [282, 287], [487, 577], [127, 187], [568, None], [130, 280], [335, 395], [184, 274]]}, {'avg': 61, 'long_permille': 375, 'max': 150, 'count': 8})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('sampled regression 20', {'end_s': 600, 'calls': [[520, None], [447, 467], [161, 221], [506, 511], [146, 296], [576, None], [73, 223], [194, 214]]}, {'avg': 63, 'long_permille': 375, 'max': 150, 'count': 8}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 34', {'end_s': 600, 'calls': [[526, 531], [100, 160], [338, None], [152, 242], [413, 433], [56, 117]]}, {'avg': 83, 'long_permille': 500, 'max': 262, 'count': 6}), ('control 37', {'end_s': 600, 'calls': [[542, 547], [483, None], [421, 418], [216, None]]}, {'avg': 126, 'long_permille': 500, 'max': 384, 'count': 4}), ('control 40', {'end_s': 600, 'calls': [[286, 346], [342, None], [309, 308], [91, 96], [519, 524], [518, None], [12, 73]]}, {'avg': 67, 'long_permille': 428, 'max': 258, 'count': 7})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('control 45', {'end_s': 600, 'calls': [[54, 204], [360, None], [102, None], [487, None], [396, None]]}, {'avg': 241, 'long_permille': 1000, 'max': 498, 'count': 5}), ('sampled regression 48', {'end_s': 600, 'calls': [[235, 234], [112, 202], [453, 498], [10, 30], [166, 186], [359, 358], [466, 471]]}, {'avg': 25, 'long_permille': 142, 'max': 90, 'count': 7}), ('sampled regression 51', {'end_s': 600, 'calls': [[553, None], [377, 422], [370, None], [180, 241]]}, {'avg': 95, 'long_permille': 500, 'max': 230, 'count': 4})]]\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":"656f06aa9d7fa9bf2d2858cde4acce908abb8d2867240c66763c14b549f56c71","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    waits = []\n    for reg, ans in x['calls']:\n        if ans is None:\n            waits.append(x['end_s'] - reg)\n        else:\n            waits.append(max(0, ans - reg))\n    if not waits:\n        return {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}\n    longs = sum(1 for w in waits if w > 60)\n    return {'avg': round(sum(waits) / len(waits)), 'long_permille': longs * 1000 // len(waits), 'max': max(waits), 'count': len(waits)}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 1', {'end_s': 600, 'calls': [[93, 138], [499, 519], [546, None], [485, None], [376, 526], [329, 419], [42, None], [303, None]]}, {'avg': 166, 'long_permille': 625, 'max': 558, 'count': 8}), ('control 4', {'end_s': 600, 'calls': [[15, None], [80, 100], [304, 324], [560, 557], [73, 78], [574, None]]}, {'avg': 109, 'long_permille': 166, 'max': 585, 'count': 6}), ('sampled regression 7', {'end_s': 600, 'calls': [[196, 216], [228, 248], [100, None], [381, 471], [370, 415], [56, 76]]}, {'avg': 115, 'long_permille': 333, 'max': 500, 'count': 6})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('control 6', {'end_s': 600, 'calls': [[541, None], [503, 502], [554, None], [543, None], [284, 434]]}, {'avg': 62, 'long_permille': 200, 'max': 150, 'count': 5}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('control 12', {'end_s': 600, 'calls': [[549, None], [34, 94], [153, 243]]}, {'avg': 67, 'long_permille': 333, 'max': 90, 'count': 3}), ('sampled regression 15', {'end_s': 600, 'calls': [[427, 472], [290, 440], [125, None], [18, 79], [88, 178], [156, 306], [7, None], [120, None]]}, {'avg': 255, 'long_permille': 875, 'max': 593, 'count': 8}), ('control 18', {'end_s': 600, 'calls': [[508, 528]]}, {'avg': 20, 'long_permille': 0, 'max': 20, 'count': 1})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('sampled regression 61', {'end_s': 600, 'calls': [[410, 415], [504, 564], [213, 258], [291, None], [359, None], [364, 369], [125, None]]}, {'avg': 162, 'long_permille': 428, 'max': 475, 'count': 7}), ('control 13', {'end_s': 600, 'calls': [[451, 511], [494, 539], [553, None], [26, None], [306, 367], [164, 314], [548, None], [406, 556]]}, {'avg': 142, 'long_permille': 500, 'max': 574, 'count': 8}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 23', {'end_s': 600, 'calls': [[121, 141], [388, None], [577, None]]}, {'avg': 85, 'long_permille': 333, 'max': 212, 'count': 3}), ('control 26', {'end_s': 600, 'calls': [[205, 225], [336, 381]]}, {'avg': 32, 'long_permille': 0, 'max': 45, 'count': 2}), ('sampled regression 29', {'end_s': 600, 'calls': [[26, 31], [282, 287], [487, 577], [127, 187], [568, None], [130, 280], [335, 395], [184, 274]]}, {'avg': 61, 'long_permille': 375, 'max': 150, 'count': 8})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('sampled regression 20', {'end_s': 600, 'calls': [[520, None], [447, 467], [161, 221], [506, 511], [146, 296], [576, None], [73, 223], [194, 214]]}, {'avg': 63, 'long_permille': 375, 'max': 150, 'count': 8}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 34', {'end_s': 600, 'calls': [[526, 531], [100, 160], [338, None], [152, 242], [413, 433], [56, 117]]}, {'avg': 83, 'long_permille': 500, 'max': 262, 'count': 6}), ('control 37', {'end_s': 600, 'calls': [[542, 547], [483, None], [421, 418], [216, None]]}, {'avg': 126, 'long_permille': 500, 'max': 384, 'count': 4}), ('control 40', {'end_s': 600, 'calls': [[286, 346], [342, None], [309, 308], [91, 96], [519, 524], [518, None], [12, 73]]}, {'avg': 67, 'long_permille': 428, 'max': 258, 'count': 7})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('control 45', {'end_s': 600, 'calls': [[54, 204], [360, None], [102, None], [487, None], [396, None]]}, {'avg': 241, 'long_permille': 1000, 'max': 498, 'count': 5}), ('sampled regression 48', {'end_s': 600, 'calls': [[235, 234], [112, 202], [453, 498], [10, 30], [166, 186], [359, 358], [466, 471]]}, {'avg': 25, 'long_permille': 142, 'max': 90, 'count': 7}), ('sampled regression 51', {'end_s': 600, 'calls': [[553, None], [377, 422], [370, None], [180, 241]]}, {'avg': 95, 'long_permille': 500, 'max': 230, 'count': 4})]]\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"},"fixed":{"sha256":"47997b14972480e68446c1a71d37b57839d05c25444bd0abf505c8385da3fd29","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    waits = []\n    for reg, ans in x['calls']:\n        if ans is None:\n            waits.append(x['end_s'] - reg)\n        else:\n            waits.append(max(0, ans - reg))\n    if not waits:\n        return {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}\n    longs = sum(1 for w in waits if w > 60)\n    return {'avg': sum(waits) // len(waits), 'long_permille': longs * 1000 // len(waits), 'max': max(waits), 'count': len(waits)}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 1', {'end_s': 600, 'calls': [[93, 138], [499, 519], [546, None], [485, None], [376, 526], [329, 419], [42, None], [303, None]]}, {'avg': 166, 'long_permille': 625, 'max': 558, 'count': 8}), ('control 4', {'end_s': 600, 'calls': [[15, None], [80, 100], [304, 324], [560, 557], [73, 78], [574, None]]}, {'avg': 109, 'long_permille': 166, 'max': 585, 'count': 6}), ('sampled regression 7', {'end_s': 600, 'calls': [[196, 216], [228, 248], [100, None], [381, 471], [370, 415], [56, 76]]}, {'avg': 115, 'long_permille': 333, 'max': 500, 'count': 6})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('control 6', {'end_s': 600, 'calls': [[541, None], [503, 502], [554, None], [543, None], [284, 434]]}, {'avg': 62, 'long_permille': 200, 'max': 150, 'count': 5}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('control 12', {'end_s': 600, 'calls': [[549, None], [34, 94], [153, 243]]}, {'avg': 67, 'long_permille': 333, 'max': 90, 'count': 3}), ('sampled regression 15', {'end_s': 600, 'calls': [[427, 472], [290, 440], [125, None], [18, 79], [88, 178], [156, 306], [7, None], [120, None]]}, {'avg': 255, 'long_permille': 875, 'max': 593, 'count': 8}), ('control 18', {'end_s': 600, 'calls': [[508, 528]]}, {'avg': 20, 'long_permille': 0, 'max': 20, 'count': 1})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('sampled regression 61', {'end_s': 600, 'calls': [[410, 415], [504, 564], [213, 258], [291, None], [359, None], [364, 369], [125, None]]}, {'avg': 162, 'long_permille': 428, 'max': 475, 'count': 7}), ('control 13', {'end_s': 600, 'calls': [[451, 511], [494, 539], [553, None], [26, None], [306, 367], [164, 314], [548, None], [406, 556]]}, {'avg': 142, 'long_permille': 500, 'max': 574, 'count': 8}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 23', {'end_s': 600, 'calls': [[121, 141], [388, None], [577, None]]}, {'avg': 85, 'long_permille': 333, 'max': 212, 'count': 3}), ('control 26', {'end_s': 600, 'calls': [[205, 225], [336, 381]]}, {'avg': 32, 'long_permille': 0, 'max': 45, 'count': 2}), ('sampled regression 29', {'end_s': 600, 'calls': [[26, 31], [282, 287], [487, 577], [127, 187], [568, None], [130, 280], [335, 395], [184, 274]]}, {'avg': 61, 'long_permille': 375, 'max': 150, 'count': 8})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('sampled regression 9', {'end_s': 600, 'calls': [[575, 595], [530, None], [76, None], [511, None], [173, 178], [76, 137], [46, 51], [370, 520]]}, {'avg': 115, 'long_permille': 625, 'max': 524, 'count': 8}), ('sampled regression 20', {'end_s': 600, 'calls': [[520, None], [447, 467], [161, 221], [506, 511], [146, 296], [576, None], [73, 223], [194, 214]]}, {'avg': 63, 'long_permille': 375, 'max': 150, 'count': 8}), ('boundary: unanswered call at the end', {'end_s': 600, 'calls': [[500, None], [10, 30]]}, {'avg': 60, 'long_permille': 500, 'max': 100, 'count': 2}), ('control 34', {'end_s': 600, 'calls': [[526, 531], [100, 160], [338, None], [152, 242], [413, 433], [56, 117]]}, {'avg': 83, 'long_permille': 500, 'max': 262, 'count': 6}), ('control 37', {'end_s': 600, 'calls': [[542, 547], [483, None], [421, 418], [216, None]]}, {'avg': 126, 'long_permille': 500, 'max': 384, 'count': 4}), ('control 40', {'end_s': 600, 'calls': [[286, 346], [342, None], [309, 308], [91, 96], [519, 524], [518, None], [12, 73]]}, {'avg': 67, 'long_permille': 428, 'max': 258, 'count': 7})], [('regression: mean with a remainder', {'end_s': 600, 'calls': [[0, 10], [0, 11], [0, 11]]}, {'avg': 10, 'long_permille': 0, 'max': 11, 'count': 3}), ('boundary: long unanswered call', {'end_s': 600, 'calls': [[400, None], [0, 10], [5, 15]]}, {'avg': 73, 'long_permille': 333, 'max': 200, 'count': 3}), ('sampled regression 27', {'end_s': 600, 'calls': [[441, None], [579, None], [47, 137], [447, None]]}, {'avg': 105, 'long_permille': 750, 'max': 159, 'count': 4}), ('boundary: wait of exactly sixty seconds', {'end_s': 600, 'calls': [[0, 60], [100, 161]]}, {'avg': 60, 'long_permille': 500, 'max': 61, 'count': 2}), ('boundary: no calls', {'end_s': 600, 'calls': []}, {'avg': 0, 'long_permille': 0, 'max': 0, 'count': 0}), ('control 45', {'end_s': 600, 'calls': [[54, 204], [360, None], [102, None], [487, None], [396, None]]}, {'avg': 241, 'long_permille': 1000, 'max': 498, 'count': 5}), ('sampled regression 48', {'end_s': 600, 'calls': [[235, 234], [112, 202], [453, 498], [10, 30], [166, 186], [359, 358], [466, 471]]}, {'avg': 25, 'long_permille': 142, 'max': 90, 'count': 7}), ('sampled regression 51', {'end_s': 600, 'calls': [[553, None], [377, 422], [370, None], [180, 241]]}, {'avg': 95, 'long_permille': 500, 'max': 230, 'count': 4})]]\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-waiting-time-statistics-mean-rounding","generated_at":"2026-09-29T14:47:53.771195+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.","repair":"Floor the mean wait.","root_cause":"The mean is rounded to nearest instead of floored.","sha256":"fa3cca85cdebf1bfdc79bc2b5ed85dba4606cb687886e98c1b78cfd76680221a","title":"Hall call waiting time statistics: mean rounding · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":43.037,"exit_code":1,"observations":[{"actual":{"avg":11,"count":3,"long_permille":0,"max":11},"check":"regression: mean with a remainder","expected":{"avg":10,"count":3,"long_permille":0,"max":11},"passed":false},{"actual":{"avg":61,"count":2,"long_permille":500,"max":61},"check":"boundary: wait of exactly sixty seconds","expected":{"avg":60,"count":2,"long_permille":500,"max":61},"passed":false},{"actual":{"avg":116,"count":8,"long_permille":625,"max":524},"check":"sampled regression 9","expected":{"avg":115,"count":8,"long_permille":625,"max":524},"passed":false},{"actual":{"avg":74,"count":3,"long_permille":333,"max":200},"check":"boundary: long unanswered call","expected":{"avg":73,"count":3,"long_permille":333,"max":200},"passed":false},{"actual":{"avg":60,"count":2,"long_permille":500,"max":100},"check":"boundary: unanswered call at the end","expected":{"avg":60,"count":2,"long_permille":500,"max":100},"passed":true},{"actual":{"avg":167,"count":8,"long_permille":625,"max":558},"check":"control 1","expected":{"avg":166,"count":8,"long_permille":625,"max":558},"passed":false},{"actual":{"avg":110,"count":6,"long_permille":166,"max":585},"check":"control 4","expected":{"avg":109,"count":6,"long_permille":166,"max":585},"passed":false},{"actual":{"avg":116,"count":6,"long_permille":333,"max":500},"check":"sampled regression 7","expected":{"avg":115,"count":6,"long_permille":333,"max":500},"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: mean with a remainder\", \"actual\": {\"avg\": 11, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"expected\": {\"avg\": 10, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"passed\": false}, {\"check\": \"boundary: wait of exactly sixty seconds\", \"actual\": {\"avg\": 61, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"passed\": false}, {\"check\": \"sampled regression 9\", \"actual\": {\"avg\": 116, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"expected\": {\"avg\": 115, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"passed\": false}, {\"check\": \"boundary: long unanswered call\", \"actual\": {\"avg\": 74, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"expected\": {\"avg\": 73, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"passed\": false}, {\"check\": \"boundary: unanswered call at the end\", \"actual\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"passed\": true}, {\"check\": \"control 1\", \"actual\": {\"avg\": 167, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"expected\": {\"avg\": 166, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"passed\": false}, {\"check\": \"control 4\", \"actual\": {\"avg\": 110, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"expected\": {\"avg\": 109, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"passed\": false}, {\"check\": \"sampled regression 7\", \"actual\": {\"avg\": 116, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"expected\": {\"avg\": 115, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":45.226,"exit_code":1,"observations":[{"actual":{"avg":11,"count":3,"long_permille":0,"max":11},"check":"regression: mean with a remainder","expected":{"avg":10,"count":3,"long_permille":0,"max":11},"passed":false},{"actual":{"avg":60,"count":2,"long_permille":500,"max":61},"check":"boundary: wait of exactly sixty seconds","expected":{"avg":60,"count":2,"long_permille":500,"max":61},"passed":true},{"actual":{"avg":116,"count":8,"long_permille":625,"max":524},"check":"sampled regression 9","expected":{"avg":115,"count":8,"long_permille":625,"max":524},"passed":false},{"actual":{"avg":73,"count":3,"long_permille":333,"max":200},"check":"boundary: long unanswered call","expected":{"avg":73,"count":3,"long_permille":333,"max":200},"passed":true},{"actual":{"avg":60,"count":2,"long_permille":500,"max":100},"check":"boundary: unanswered call at the end","expected":{"avg":60,"count":2,"long_permille":500,"max":100},"passed":true},{"actual":{"avg":166,"count":8,"long_permille":625,"max":558},"check":"control 1","expected":{"avg":166,"count":8,"long_permille":625,"max":558},"passed":true},{"actual":{"avg":109,"count":6,"long_permille":166,"max":585},"check":"control 4","expected":{"avg":109,"count":6,"long_permille":166,"max":585},"passed":true},{"actual":{"avg":116,"count":6,"long_permille":333,"max":500},"check":"sampled regression 7","expected":{"avg":115,"count":6,"long_permille":333,"max":500},"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: mean with a remainder\", \"actual\": {\"avg\": 11, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"expected\": {\"avg\": 10, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"passed\": false}, {\"check\": \"boundary: wait of exactly sixty seconds\", \"actual\": {\"avg\": 60, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"passed\": true}, {\"check\": \"sampled regression 9\", \"actual\": {\"avg\": 116, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"expected\": {\"avg\": 115, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"passed\": false}, {\"check\": \"boundary: long unanswered call\", \"actual\": {\"avg\": 73, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"expected\": {\"avg\": 73, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"passed\": true}, {\"check\": \"boundary: unanswered call at the end\", \"actual\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"passed\": true}, {\"check\": \"control 1\", \"actual\": {\"avg\": 166, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"expected\": {\"avg\": 166, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"passed\": true}, {\"check\": \"control 4\", \"actual\": {\"avg\": 109, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"expected\": {\"avg\": 109, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"passed\": true}, {\"check\": \"sampled regression 7\", \"actual\": {\"avg\": 116, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"expected\": {\"avg\": 115, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":41.629,"exit_code":0,"observations":[{"actual":{"avg":10,"count":3,"long_permille":0,"max":11},"check":"regression: mean with a remainder","expected":{"avg":10,"count":3,"long_permille":0,"max":11},"passed":true},{"actual":{"avg":60,"count":2,"long_permille":500,"max":61},"check":"boundary: wait of exactly sixty seconds","expected":{"avg":60,"count":2,"long_permille":500,"max":61},"passed":true},{"actual":{"avg":115,"count":8,"long_permille":625,"max":524},"check":"sampled regression 9","expected":{"avg":115,"count":8,"long_permille":625,"max":524},"passed":true},{"actual":{"avg":73,"count":3,"long_permille":333,"max":200},"check":"boundary: long unanswered call","expected":{"avg":73,"count":3,"long_permille":333,"max":200},"passed":true},{"actual":{"avg":60,"count":2,"long_permille":500,"max":100},"check":"boundary: unanswered call at the end","expected":{"avg":60,"count":2,"long_permille":500,"max":100},"passed":true},{"actual":{"avg":166,"count":8,"long_permille":625,"max":558},"check":"control 1","expected":{"avg":166,"count":8,"long_permille":625,"max":558},"passed":true},{"actual":{"avg":109,"count":6,"long_permille":166,"max":585},"check":"control 4","expected":{"avg":109,"count":6,"long_permille":166,"max":585},"passed":true},{"actual":{"avg":115,"count":6,"long_permille":333,"max":500},"check":"sampled regression 7","expected":{"avg":115,"count":6,"long_permille":333,"max":500},"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: mean with a remainder\", \"actual\": {\"avg\": 10, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"expected\": {\"avg\": 10, \"long_permille\": 0, \"max\": 11, \"count\": 3}, \"passed\": true}, {\"check\": \"boundary: wait of exactly sixty seconds\", \"actual\": {\"avg\": 60, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 61, \"count\": 2}, \"passed\": true}, {\"check\": \"sampled regression 9\", \"actual\": {\"avg\": 115, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"expected\": {\"avg\": 115, \"long_permille\": 625, \"max\": 524, \"count\": 8}, \"passed\": true}, {\"check\": \"boundary: long unanswered call\", \"actual\": {\"avg\": 73, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"expected\": {\"avg\": 73, \"long_permille\": 333, \"max\": 200, \"count\": 3}, \"passed\": true}, {\"check\": \"boundary: unanswered call at the end\", \"actual\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"expected\": {\"avg\": 60, \"long_permille\": 500, \"max\": 100, \"count\": 2}, \"passed\": true}, {\"check\": \"control 1\", \"actual\": {\"avg\": 166, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"expected\": {\"avg\": 166, \"long_permille\": 625, \"max\": 558, \"count\": 8}, \"passed\": true}, {\"check\": \"control 4\", \"actual\": {\"avg\": 109, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"expected\": {\"avg\": 109, \"long_permille\": 166, \"max\": 585, \"count\": 6}, \"passed\": true}, {\"check\": \"sampled regression 7\", \"actual\": {\"avg\": 115, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"expected\": {\"avg\": 115, \"long_permille\": 333, \"max\": 500, \"count\": 6}, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}