{"abstract":"Highway segments are charged twice.","category":"Ride-hailing fare and surge pricing","checks":7,"contract":"A single-tariff taximeter bills each segment [seconds, meters] by distance when its speed is at least v m/s (meters >= v*seconds, so a zero-duration movement bills distance) and by time otherwise, never both. Charges accumulate exactly (per_km per 1000 m, per_hour per 3600 s) and the total is rounded half up to a cent once, then the flag fall is added.","evaluation_group":"w2-ride-hailing-fare-surge-taximeter-single-tariff","failed_approach":"Charging the larger of the two is the double-tariff rule, not the single tariff.","family":"w2-ride-hailing-fare-surge-taximeter-single-tariff-single-tariff-exclusivity","id":"FA-85766","implementations":{"attempt":{"sha256":"337073f79e80ab76567cb86f61354423ed8ebef1935ee01711d83b56d1dbbd29","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(segments, rate):\n    acc = Fraction(0)\n    for dt, dm in segments:\n        acc += max(Fraction(dm * rate['per_km'], 1000), Fraction(dt * rate['per_hour'], 3600))\n    cents = int(acc * 2 + 1) // 2\n    return rate['flag'] + cents\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: single tariff exclusivity',\n   [[[0, 3], [0, 3], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 245, 'v': 5}], 382),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 0], [10, 20], [10, 50], [10, 110], [10, 53]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   449),\n  ('second regression',\n   [[[30, 150], [1, 0], [5, 10], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 353),\n  ('normal control 1', [[[0, 0], [0, 7]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 302),\n  ('normal control 2',\n   [[[0, 7], [0, 0], [0, 0], [0, 0], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 313),\n  ('normal control 3', [[[1, 0], [0, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 303),\n  ('normal control 4', [[[10, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 400)],\n [('regression: single tariff exclusivity',\n   [[[0, 0], [5, 0], [10, 50], [10, 110]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 435),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [10, 49], [10, 7], [30, 153], [1, 4], [0, 3]],\n    {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   460),\n  ('second regression',\n   [[[30, 7], [0, 7], [1, 8], [10, 0], [5, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 245, 'v': 5}],\n   439),\n  ('normal control 1', [[[1, 4], [10, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 402),\n  ('normal control 2', [[[5, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 395),\n  ('normal control 3', [[[10, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 400),\n  ('normal control 4', [[[1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 301)],\n [('regression: single tariff exclusivity',\n   [[[5, 25]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 396),\n  ('partial repair probe: single tariff exclusivity',\n   [[[1, 7], [5, 28], [10, 50], [5, 24], [10, 20]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}],\n   427),\n  ('second regression',\n   [[[0, 7], [0, 0], [0, 7], [10, 53], [0, 0], [10, 50]],\n    {'flag': 300, 'per_hour': 3900, 'per_km': 230, 'v': 5}],\n   327),\n  ('normal control 1', [[[10, 7], [0, 0], [1, 0]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   311),\n  ('normal control 2',\n   [[[0, 7], [30, 7], [0, 0], [5, 0], [1, 4]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 341),\n  ('normal control 3',\n   [[[5, 7], [10, 20], [10, 49], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 363),\n  ('normal control 4', [[[5, 7], [1, 2]], {'flag': 300, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 307)],\n [('regression: single tariff exclusivity',\n   [[[10, 0], [5, 24], [1, 2], [0, 0], [10, 0], [5, 55]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   429),\n  ('partial repair probe: single tariff exclusivity',\n   [[[30, 149], [10, 7], [1, 8], [30, 0], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   448),\n  ('second regression',\n   [[[10, 110], [10, 49], [10, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 438),\n  ('normal control 1',\n   [[[30, 60], [5, 24], [1, 0], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 376),\n  ('normal control 2', [[[5, 0], [0, 3], [1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}],\n   308),\n  ('normal control 3', [[[0, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 300),\n  ('normal control 4', [[[10, 20]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 310)],\n [('regression: single tariff exclusivity',\n   [[[10, 50], [10, 50], [10, 7], [30, 149], [5, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 245, 'v': 5}],\n   376),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [30, 149], [5, 0], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 351),\n  ('second regression', [[[0, 0], [5, 0], [10, 53]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}],\n   408),\n  ('normal control 1', [[[30, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 425),\n  ('normal control 2', [[[0, 3], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 301),\n  ('normal control 3', [[[10, 0]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 401),\n  ('normal control 4', [[[0, 0], [0, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 392)]]\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":"80fa470b0f418fc9a38a87378e759bc661815f6702aef3dc12e6dad8d84621fb","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(segments, rate):\n    acc = Fraction(0)\n    for dt, dm in segments:\n        if dm >= rate['v'] * dt:\n            acc += Fraction(dm * rate['per_km'], 1000)\n        acc += Fraction(dt * rate['per_hour'], 3600)\n    cents = int(acc * 2 + 1) // 2\n    return rate['flag'] + cents\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: single tariff exclusivity',\n   [[[0, 3], [0, 3], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 245, 'v': 5}], 382),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 0], [10, 20], [10, 50], [10, 110], [10, 53]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   449),\n  ('second regression',\n   [[[30, 150], [1, 0], [5, 10], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 353),\n  ('normal control 1', [[[0, 0], [0, 7]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 302),\n  ('normal control 2',\n   [[[0, 7], [0, 0], [0, 0], [0, 0], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 313),\n  ('normal control 3', [[[1, 0], [0, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 303),\n  ('normal control 4', [[[10, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 400)],\n [('regression: single tariff exclusivity',\n   [[[0, 0], [5, 0], [10, 50], [10, 110]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 435),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [10, 49], [10, 7], [30, 153], [1, 4], [0, 3]],\n    {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   460),\n  ('second regression',\n   [[[30, 7], [0, 7], [1, 8], [10, 0], [5, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 245, 'v': 5}],\n   439),\n  ('normal control 1', [[[1, 4], [10, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 402),\n  ('normal control 2', [[[5, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 395),\n  ('normal control 3', [[[10, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 400),\n  ('normal control 4', [[[1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 301)],\n [('regression: single tariff exclusivity',\n   [[[5, 25]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 396),\n  ('partial repair probe: single tariff exclusivity',\n   [[[1, 7], [5, 28], [10, 50], [5, 24], [10, 20]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}],\n   427),\n  ('second regression',\n   [[[0, 7], [0, 0], [0, 7], [10, 53], [0, 0], [10, 50]],\n    {'flag': 300, 'per_hour': 3900, 'per_km': 230, 'v': 5}],\n   327),\n  ('normal control 1', [[[10, 7], [0, 0], [1, 0]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   311),\n  ('normal control 2',\n   [[[0, 7], [30, 7], [0, 0], [5, 0], [1, 4]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 341),\n  ('normal control 3',\n   [[[5, 7], [10, 20], [10, 49], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 363),\n  ('normal control 4', [[[5, 7], [1, 2]], {'flag': 300, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 307)],\n [('regression: single tariff exclusivity',\n   [[[10, 0], [5, 24], [1, 2], [0, 0], [10, 0], [5, 55]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   429),\n  ('partial repair probe: single tariff exclusivity',\n   [[[30, 149], [10, 7], [1, 8], [30, 0], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   448),\n  ('second regression',\n   [[[10, 110], [10, 49], [10, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 438),\n  ('normal control 1',\n   [[[30, 60], [5, 24], [1, 0], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 376),\n  ('normal control 2', [[[5, 0], [0, 3], [1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}],\n   308),\n  ('normal control 3', [[[0, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 300),\n  ('normal control 4', [[[10, 20]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 310)],\n [('regression: single tariff exclusivity',\n   [[[10, 50], [10, 50], [10, 7], [30, 149], [5, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 245, 'v': 5}],\n   376),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [30, 149], [5, 0], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 351),\n  ('second regression', [[[0, 0], [5, 0], [10, 53]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}],\n   408),\n  ('normal control 1', [[[30, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 425),\n  ('normal control 2', [[[0, 3], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 301),\n  ('normal control 3', [[[10, 0]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 401),\n  ('normal control 4', [[[0, 0], [0, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 392)]]\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":"5e3f6730ca1ec5a987c1176653faf978db0d55a29beca13f740d54ac235fda47","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(segments, rate):\n    acc = Fraction(0)\n    for dt, dm in segments:\n        if dm >= rate['v'] * dt:\n            acc += Fraction(dm * rate['per_km'], 1000)\n        else:\n            acc += Fraction(dt * rate['per_hour'], 3600)\n    cents = int(acc * 2 + 1) // 2\n    return rate['flag'] + cents\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: single tariff exclusivity',\n   [[[0, 3], [0, 3], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 245, 'v': 5}], 382),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 0], [10, 20], [10, 50], [10, 110], [10, 53]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   449),\n  ('second regression',\n   [[[30, 150], [1, 0], [5, 10], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 353),\n  ('normal control 1', [[[0, 0], [0, 7]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 302),\n  ('normal control 2',\n   [[[0, 7], [0, 0], [0, 0], [0, 0], [10, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 313),\n  ('normal control 3', [[[1, 0], [0, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 303),\n  ('normal control 4', [[[10, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 400)],\n [('regression: single tariff exclusivity',\n   [[[0, 0], [5, 0], [10, 50], [10, 110]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 435),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [10, 49], [10, 7], [30, 153], [1, 4], [0, 3]],\n    {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   460),\n  ('second regression',\n   [[[30, 7], [0, 7], [1, 8], [10, 0], [5, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 245, 'v': 5}],\n   439),\n  ('normal control 1', [[[1, 4], [10, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 402),\n  ('normal control 2', [[[5, 0]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 395),\n  ('normal control 3', [[[10, 7]], {'flag': 390, 'per_hour': 3600, 'per_km': 199, 'v': 5}], 400),\n  ('normal control 4', [[[1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 301)],\n [('regression: single tariff exclusivity',\n   [[[5, 25]], {'flag': 390, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 396),\n  ('partial repair probe: single tariff exclusivity',\n   [[[1, 7], [5, 28], [10, 50], [5, 24], [10, 20]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}],\n   427),\n  ('second regression',\n   [[[0, 7], [0, 0], [0, 7], [10, 53], [0, 0], [10, 50]],\n    {'flag': 300, 'per_hour': 3900, 'per_km': 230, 'v': 5}],\n   327),\n  ('normal control 1', [[[10, 7], [0, 0], [1, 0]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   311),\n  ('normal control 2',\n   [[[0, 7], [30, 7], [0, 0], [5, 0], [1, 4]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 341),\n  ('normal control 3',\n   [[[5, 7], [10, 20], [10, 49], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 363),\n  ('normal control 4', [[[5, 7], [1, 2]], {'flag': 300, 'per_hour': 3900, 'per_km': 199, 'v': 5}], 307)],\n [('regression: single tariff exclusivity',\n   [[[10, 0], [5, 24], [1, 2], [0, 0], [10, 0], [5, 55]],\n    {'flag': 390, 'per_hour': 3900, 'per_km': 199, 'v': 5}],\n   429),\n  ('partial repair probe: single tariff exclusivity',\n   [[[30, 149], [10, 7], [1, 8], [30, 0], [30, 330]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}],\n   448),\n  ('second regression',\n   [[[10, 110], [10, 49], [10, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 438),\n  ('normal control 1',\n   [[[30, 60], [5, 24], [1, 0], [30, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 376),\n  ('normal control 2', [[[5, 0], [0, 3], [1, 4]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}],\n   308),\n  ('normal control 3', [[[0, 0]], {'flag': 300, 'per_hour': 4150, 'per_km': 199, 'v': 5}], 300),\n  ('normal control 4', [[[10, 20]], {'flag': 300, 'per_hour': 3600, 'per_km': 230, 'v': 5}], 310)],\n [('regression: single tariff exclusivity',\n   [[[10, 50], [10, 50], [10, 7], [30, 149], [5, 7]], {'flag': 300, 'per_hour': 4150, 'per_km': 245, 'v': 5}],\n   376),\n  ('partial repair probe: single tariff exclusivity',\n   [[[5, 55], [30, 149], [5, 0], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 351),\n  ('second regression', [[[0, 0], [5, 0], [10, 53]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}],\n   408),\n  ('normal control 1', [[[30, 7]], {'flag': 390, 'per_hour': 4150, 'per_km': 230, 'v': 5}], 425),\n  ('normal control 2', [[[0, 3], [0, 0]], {'flag': 300, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 301),\n  ('normal control 3', [[[10, 0]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 401),\n  ('normal control 4', [[[0, 0], [0, 7]], {'flag': 390, 'per_hour': 3900, 'per_km': 245, 'v': 5}], 392)]]\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 toy pricing contract stipulated for this example; it does not reproduce the pricing of any real ride-hailing operator or regulator. 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-ride-hailing-fare-surge-taximeter-single-tariff-single-tariff-exclusivity","generated_at":"2026-09-29T14:50:43.474822+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Ride-hailing prices are computed per trip at scale; ordering, unit and boundary slips become systematic over- or under-charging.","repair":"Bill exactly one of distance or time per segment.","root_cause":"The time charge is added unconditionally, not only below the switch speed.","sha256":"ccdc054a3be0c946bb28bb8e6685924d506a2e5bdff7989a509ffa69f9684373","title":"Fast segments billed for distance and time · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":42.238,"exit_code":1,"observations":[{"actual":382,"check":"regression: single tariff exclusivity","expected":382,"passed":true},{"actual":450,"check":"partial repair probe: single tariff exclusivity","expected":449,"passed":false},{"actual":353,"check":"second regression","expected":353,"passed":true},{"actual":302,"check":"normal control 1","expected":302,"passed":true},{"actual":313,"check":"normal control 2","expected":313,"passed":true},{"actual":303,"check":"normal control 3","expected":303,"passed":true},{"actual":400,"check":"normal control 4","expected":400,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: single tariff exclusivity\", \"actual\": 382, \"expected\": 382, \"passed\": true}, {\"check\": \"partial repair probe: single tariff exclusivity\", \"actual\": 450, \"expected\": 449, \"passed\": false}, {\"check\": \"second regression\", \"actual\": 353, \"expected\": 353, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 302, \"expected\": 302, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 313, \"expected\": 313, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 303, \"expected\": 303, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 400, \"expected\": 400, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":43.317,"exit_code":1,"observations":[{"actual":412,"check":"regression: single tariff exclusivity","expected":382,"passed":false},{"actual":481,"check":"partial repair probe: single tariff exclusivity","expected":449,"passed":false},{"actual":388,"check":"second regression","expected":353,"passed":false},{"actual":302,"check":"normal control 1","expected":302,"passed":true},{"actual":313,"check":"normal control 2","expected":313,"passed":true},{"actual":303,"check":"normal control 3","expected":303,"passed":true},{"actual":400,"check":"normal control 4","expected":400,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: single tariff exclusivity\", \"actual\": 412, \"expected\": 382, \"passed\": false}, {\"check\": \"partial repair probe: single tariff exclusivity\", \"actual\": 481, \"expected\": 449, \"passed\": false}, {\"check\": \"second regression\", \"actual\": 388, \"expected\": 353, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": 302, \"expected\": 302, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 313, \"expected\": 313, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 303, \"expected\": 303, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 400, \"expected\": 400, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":44.449,"exit_code":0,"observations":[{"actual":382,"check":"regression: single tariff exclusivity","expected":382,"passed":true},{"actual":449,"check":"partial repair probe: single tariff exclusivity","expected":449,"passed":true},{"actual":353,"check":"second regression","expected":353,"passed":true},{"actual":302,"check":"normal control 1","expected":302,"passed":true},{"actual":313,"check":"normal control 2","expected":313,"passed":true},{"actual":303,"check":"normal control 3","expected":303,"passed":true},{"actual":400,"check":"normal control 4","expected":400,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: single tariff exclusivity\", \"actual\": 382, \"expected\": 382, \"passed\": true}, {\"check\": \"partial repair probe: single tariff exclusivity\", \"actual\": 449, \"expected\": 449, \"passed\": true}, {\"check\": \"second regression\", \"actual\": 353, \"expected\": 353, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 302, \"expected\": 302, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 313, \"expected\": 313, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 303, \"expected\": 303, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 400, \"expected\": 400, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}