{"abstract":"A minimum-fare trip is charged the minimum plus the base fare.","category":"Ride-hailing fare and surge pricing","checks":7,"contract":"All money is integer cents. Distance charge = meters x per_km / 1000 and time charge = seconds x per_min / 60, each rounded half up to a cent on its own. Subtotal = base + distance + time. The minimum fare applies to that subtotal only; the booking fee is added after the minimum. Return the distance charge, time charge and fare.","contract_signature":"trip, rate","evaluation_group":"w2-ride-hailing-fare-surge-metered-fare","failed_approach":"Raising the minimum by the base fare charges the same inflated floor.","family":"w2-ride-hailing-fare-surge-metered-fare-base-inside-minimum","id":"FA-85356","implementations":{"attempt":{"sha256":"6a441771108d7671295a8f0db02d56c45757d60eb6caa1009770aa25395dad1e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(trip, rate):\n    def half_up(num, den):\n        return (num * 2 + den) // (den * 2)\n    dist = half_up(trip['meters'] * rate['per_km'], 1000)\n    tm = half_up(trip['seconds'] * rate['per_min'], 60)\n    sub = rate['base'] + dist + tm\n    fare = max(sub, rate['minimum'] + rate['base']) + rate['booking_fee']\n    return {'distance': dist, 'time': tm, 'fare': fare}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 1629},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 95, 'per_min': 25}],\n   {'distance': 0, 'fare': 1250, 'time': 679}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 2500, 'seconds': 0},\n    {'base': 150, 'booking_fee': 250, 'minimum': 700, 'per_km': 95, 'per_min': 30}],\n   {'distance': 238, 'fare': 950, 'time': 0}),\n  ('second regression',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 150, 'booking_fee': 250, 'minimum': 500, 'per_km': 250, 'per_min': 35}],\n   {'distance': 0, 'fare': 750, 'time': 36}),\n  ('normal control 1',\n   [{'meters': 14115, 'seconds': 90},\n    {'base': 250, 'booking_fee': 0, 'minimum': 1000, 'per_km': 125, 'per_min': 30}],\n   {'distance': 1764, 'fare': 2059, 'time': 45}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 121},\n    {'base': 0, 'booking_fee': 0, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 125, 'fare': 700, 'time': 71}),\n  ('normal control 3',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 0, 'booking_fee': 0, 'minimum': 1000, 'per_km': 250, 'per_min': 35}],\n   {'distance': 0, 'fare': 1000, 'time': 36}),\n  ('normal control 4',\n   [{'meters': 6825, 'seconds': 61},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 250, 'per_min': 30}],\n   {'distance': 1706, 'fare': 2237, 'time': 31})],\n [('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 35}],\n   {'distance': 0, 'fare': 750, 'time': 36}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 150, 'booking_fee': 175, 'minimum': 1000, 'per_km': 110, 'per_min': 35}],\n   {'distance': 0, 'fare': 1175, 'time': 36}),\n  ('second regression',\n   [{'meters': 4, 'seconds': 0},\n    {'base': 150, 'booking_fee': 250, 'minimum': 700, 'per_km': 125, 'per_min': 35}],\n   {'distance': 1, 'fare': 950, 'time': 0}),\n  ('normal control 1',\n   [{'meters': 21815, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 1000, 'per_km': 125, 'per_min': 25}],\n   {'distance': 2727, 'fare': 3002, 'time': 25}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 0},\n    {'base': 0, 'booking_fee': 0, 'minimum': 500, 'per_km': 250, 'per_min': 25}],\n   {'distance': 125, 'fare': 500, 'time': 0}),\n  ('normal control 3',\n   [{'meters': 0, 'seconds': 90},\n    {'base': 0, 'booking_fee': 250, 'minimum': 500, 'per_km': 110, 'per_min': 30}],\n   {'distance': 0, 'fare': 750, 'time': 45}),\n  ('normal control 4',\n   [{'meters': 12, 'seconds': 90},\n    {'base': 0, 'booking_fee': 175, 'minimum': 700, 'per_km': 250, 'per_min': 30}],\n   {'distance': 3, 'fare': 875, 'time': 45})],\n [('regression: base inside minimum',\n   [{'meters': 0, 'seconds': 90},\n    {'base': 150, 'booking_fee': 250, 'minimum': 500, 'per_km': 110, 'per_min': 25}],\n   {'distance': 0, 'fare': 750, 'time': 38}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 700, 'per_km': 110, 'per_min': 30}],\n   {'distance': 0, 'fare': 700, 'time': 31}),\n  ('second regression',\n   [{'meters': 12, 'seconds': 214},\n    {'base': 250, 'booking_fee': 175, 'minimum': 700, 'per_km': 95, 'per_min': 25}],\n   {'distance': 1, 'fare': 875, 'time': 89}),\n  ('normal control 1',\n   [{'meters': 0, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 110, 'per_min': 15}],\n   {'distance': 0, 'fare': 950, 'time': 8}),\n  ('normal control 2',\n   [{'meters': 11380, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 2845, 'fare': 3113, 'time': 18}),\n  ('normal control 3',\n   [{'meters': 14883, 'seconds': 245},\n    {'base': 150, 'booking_fee': 175, 'minimum': 500, 'per_km': 125, 'per_min': 30}],\n   {'distance': 1860, 'fare': 2308, 'time': 123}),\n  ('normal control 4',\n   [{'meters': 17188, 'seconds': 0},\n    {'base': 250, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 35}],\n   {'distance': 1633, 'fare': 2133, 'time': 0})],\n [('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 175, 'minimum': 1000, 'per_km': 95, 'per_min': 30}],\n   {'distance': 0, 'fare': 1175, 'time': 31}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 0, 'seconds': 30},\n    {'base': 250, 'booking_fee': 250, 'minimum': 700, 'per_km': 95, 'per_min': 25}],\n   {'distance': 0, 'fare': 950, 'time': 13}),\n  ('second regression',\n   [{'meters': 1004, 'seconds': 90},\n    {'base': 150, 'booking_fee': 0, 'minimum': 500, 'per_km': 110, 'per_min': 25}],\n   {'distance': 110, 'fare': 500, 'time': 38}),\n  ('normal control 1',\n   [{'meters': 500, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 125, 'per_min': 15}],\n   {'distance': 63, 'fare': 950, 'time': 8}),\n  ('normal control 2',\n   [{'meters': 12, 'seconds': 0}, {'base': 0, 'booking_fee': 0, 'minimum': 700, 'per_km': 95, 'per_min': 15}],\n   {'distance': 1, 'fare': 700, 'time': 0}),\n  ('normal control 3',\n   [{'meters': 4, 'seconds': 0},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 1, 'fare': 950, 'time': 0}),\n  ('normal control 4',\n   [{'meters': 2500, 'seconds': 0},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 625, 'fare': 950, 'time': 0})],\n [('regression: base inside minimum',\n   [{'meters': 500, 'seconds': 30},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 110, 'per_min': 30}],\n   {'distance': 55, 'fare': 1250, 'time': 15}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 2500, 'seconds': 30},\n    {'base': 250, 'booking_fee': 0, 'minimum': 500, 'per_km': 125, 'per_min': 25}],\n   {'distance': 313, 'fare': 576, 'time': 13}),\n  ('second regression',\n   [{'meters': 500, 'seconds': 61},\n    {'base': 250, 'booking_fee': 175, 'minimum': 700, 'per_km': 250, 'per_min': 15}],\n   {'distance': 125, 'fare': 875, 'time': 15}),\n  ('normal control 1',\n   [{'meters': 500, 'seconds': 1622},\n    {'base': 250, 'booking_fee': 175, 'minimum': 500, 'per_km': 250, 'per_min': 15}],\n   {'distance': 125, 'fare': 956, 'time': 406}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 90},\n    {'base': 0, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 15}],\n   {'distance': 48, 'fare': 750, 'time': 23}),\n  ('normal control 3',\n   [{'meters': 15947, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 700, 'per_km': 125, 'per_min': 15}],\n   {'distance': 1993, 'fare': 2258, 'time': 15}),\n  ('normal control 4',\n   [{'meters': 2500, 'seconds': 2303},\n    {'base': 150, 'booking_fee': 250, 'minimum': 1000, 'per_km': 125, 'per_min': 25}],\n   {'distance': 313, 'fare': 1673, 'time': 960})]]\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":"8037704722afe759c656edd107e46f972fc3a890a8e8e9eceba92a5ccedcb1db","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(trip, rate):\n    def half_up(num, den):\n        return (num * 2 + den) // (den * 2)\n    dist = half_up(trip['meters'] * rate['per_km'], 1000)\n    tm = half_up(trip['seconds'] * rate['per_min'], 60)\n    sub = dist + tm\n    fare = max(sub, rate['minimum']) + rate['base'] + rate['booking_fee']\n    return {'distance': dist, 'time': tm, 'fare': fare}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 1629},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 95, 'per_min': 25}],\n   {'distance': 0, 'fare': 1250, 'time': 679}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 2500, 'seconds': 0},\n    {'base': 150, 'booking_fee': 250, 'minimum': 700, 'per_km': 95, 'per_min': 30}],\n   {'distance': 238, 'fare': 950, 'time': 0}),\n  ('second regression',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 150, 'booking_fee': 250, 'minimum': 500, 'per_km': 250, 'per_min': 35}],\n   {'distance': 0, 'fare': 750, 'time': 36}),\n  ('normal control 1',\n   [{'meters': 14115, 'seconds': 90},\n    {'base': 250, 'booking_fee': 0, 'minimum': 1000, 'per_km': 125, 'per_min': 30}],\n   {'distance': 1764, 'fare': 2059, 'time': 45}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 121},\n    {'base': 0, 'booking_fee': 0, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 125, 'fare': 700, 'time': 71}),\n  ('normal control 3',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 0, 'booking_fee': 0, 'minimum': 1000, 'per_km': 250, 'per_min': 35}],\n   {'distance': 0, 'fare': 1000, 'time': 36}),\n  ('normal control 4',\n   [{'meters': 6825, 'seconds': 61},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 250, 'per_min': 30}],\n   {'distance': 1706, 'fare': 2237, 'time': 31})],\n [('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 35}],\n   {'distance': 0, 'fare': 750, 'time': 36}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 0, 'seconds': 61},\n    {'base': 150, 'booking_fee': 175, 'minimum': 1000, 'per_km': 110, 'per_min': 35}],\n   {'distance': 0, 'fare': 1175, 'time': 36}),\n  ('second regression',\n   [{'meters': 4, 'seconds': 0},\n    {'base': 150, 'booking_fee': 250, 'minimum': 700, 'per_km': 125, 'per_min': 35}],\n   {'distance': 1, 'fare': 950, 'time': 0}),\n  ('normal control 1',\n   [{'meters': 21815, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 1000, 'per_km': 125, 'per_min': 25}],\n   {'distance': 2727, 'fare': 3002, 'time': 25}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 0},\n    {'base': 0, 'booking_fee': 0, 'minimum': 500, 'per_km': 250, 'per_min': 25}],\n   {'distance': 125, 'fare': 500, 'time': 0}),\n  ('normal control 3',\n   [{'meters': 0, 'seconds': 90},\n    {'base': 0, 'booking_fee': 250, 'minimum': 500, 'per_km': 110, 'per_min': 30}],\n   {'distance': 0, 'fare': 750, 'time': 45}),\n  ('normal control 4',\n   [{'meters': 12, 'seconds': 90},\n    {'base': 0, 'booking_fee': 175, 'minimum': 700, 'per_km': 250, 'per_min': 30}],\n   {'distance': 3, 'fare': 875, 'time': 45})],\n [('regression: base inside minimum',\n   [{'meters': 0, 'seconds': 90},\n    {'base': 150, 'booking_fee': 250, 'minimum': 500, 'per_km': 110, 'per_min': 25}],\n   {'distance': 0, 'fare': 750, 'time': 38}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 700, 'per_km': 110, 'per_min': 30}],\n   {'distance': 0, 'fare': 700, 'time': 31}),\n  ('second regression',\n   [{'meters': 12, 'seconds': 214},\n    {'base': 250, 'booking_fee': 175, 'minimum': 700, 'per_km': 95, 'per_min': 25}],\n   {'distance': 1, 'fare': 875, 'time': 89}),\n  ('normal control 1',\n   [{'meters': 0, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 110, 'per_min': 15}],\n   {'distance': 0, 'fare': 950, 'time': 8}),\n  ('normal control 2',\n   [{'meters': 11380, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 2845, 'fare': 3113, 'time': 18}),\n  ('normal control 3',\n   [{'meters': 14883, 'seconds': 245},\n    {'base': 150, 'booking_fee': 175, 'minimum': 500, 'per_km': 125, 'per_min': 30}],\n   {'distance': 1860, 'fare': 2308, 'time': 123}),\n  ('normal control 4',\n   [{'meters': 17188, 'seconds': 0},\n    {'base': 250, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 35}],\n   {'distance': 1633, 'fare': 2133, 'time': 0})],\n [('regression: base inside minimum',\n   [{'meters': 4, 'seconds': 61},\n    {'base': 250, 'booking_fee': 175, 'minimum': 1000, 'per_km': 95, 'per_min': 30}],\n   {'distance': 0, 'fare': 1175, 'time': 31}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 0, 'seconds': 30},\n    {'base': 250, 'booking_fee': 250, 'minimum': 700, 'per_km': 95, 'per_min': 25}],\n   {'distance': 0, 'fare': 950, 'time': 13}),\n  ('second regression',\n   [{'meters': 1004, 'seconds': 90},\n    {'base': 150, 'booking_fee': 0, 'minimum': 500, 'per_km': 110, 'per_min': 25}],\n   {'distance': 110, 'fare': 500, 'time': 38}),\n  ('normal control 1',\n   [{'meters': 500, 'seconds': 30},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 125, 'per_min': 15}],\n   {'distance': 63, 'fare': 950, 'time': 8}),\n  ('normal control 2',\n   [{'meters': 12, 'seconds': 0}, {'base': 0, 'booking_fee': 0, 'minimum': 700, 'per_km': 95, 'per_min': 15}],\n   {'distance': 1, 'fare': 700, 'time': 0}),\n  ('normal control 3',\n   [{'meters': 4, 'seconds': 0},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 1, 'fare': 950, 'time': 0}),\n  ('normal control 4',\n   [{'meters': 2500, 'seconds': 0},\n    {'base': 0, 'booking_fee': 250, 'minimum': 700, 'per_km': 250, 'per_min': 35}],\n   {'distance': 625, 'fare': 950, 'time': 0})],\n [('regression: base inside minimum',\n   [{'meters': 500, 'seconds': 30},\n    {'base': 250, 'booking_fee': 250, 'minimum': 1000, 'per_km': 110, 'per_min': 30}],\n   {'distance': 55, 'fare': 1250, 'time': 15}),\n  ('partial repair probe: base inside minimum',\n   [{'meters': 2500, 'seconds': 30},\n    {'base': 250, 'booking_fee': 0, 'minimum': 500, 'per_km': 125, 'per_min': 25}],\n   {'distance': 313, 'fare': 576, 'time': 13}),\n  ('second regression',\n   [{'meters': 500, 'seconds': 61},\n    {'base': 250, 'booking_fee': 175, 'minimum': 700, 'per_km': 250, 'per_min': 15}],\n   {'distance': 125, 'fare': 875, 'time': 15}),\n  ('normal control 1',\n   [{'meters': 500, 'seconds': 1622},\n    {'base': 250, 'booking_fee': 175, 'minimum': 500, 'per_km': 250, 'per_min': 15}],\n   {'distance': 125, 'fare': 956, 'time': 406}),\n  ('normal control 2',\n   [{'meters': 500, 'seconds': 90},\n    {'base': 0, 'booking_fee': 250, 'minimum': 500, 'per_km': 95, 'per_min': 15}],\n   {'distance': 48, 'fare': 750, 'time': 23}),\n  ('normal control 3',\n   [{'meters': 15947, 'seconds': 61},\n    {'base': 250, 'booking_fee': 0, 'minimum': 700, 'per_km': 125, 'per_min': 15}],\n   {'distance': 1993, 'fare': 2258, 'time': 15}),\n  ('normal control 4',\n   [{'meters': 2500, 'seconds': 2303},\n    {'base': 150, 'booking_fee': 250, 'minimum': 1000, 'per_km': 125, 'per_min': 25}],\n   {'distance': 313, 'fare': 1673, 'time': 960})]]\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-metered-fare-base-inside-minimum","generated_at":"2026-09-29T14:50:39.640673+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.","root_cause":"The base fare is excluded from the subtotal compared with the minimum and added afterwards.","sha256":"045ee31b958d85c3c4d52416507753225b2bd21417e819c7273974a65b3a86b9","title":"Base fare added on top of the minimum · 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":41.29,"exit_code":1,"observations":[{"actual":{"distance":0,"fare":1500,"time":679},"check":"regression: base inside minimum","expected":{"distance":0,"fare":1250,"time":679},"passed":false},{"actual":{"distance":238,"fare":1100,"time":0},"check":"partial repair probe: base inside minimum","expected":{"distance":238,"fare":950,"time":0},"passed":false},{"actual":{"distance":0,"fare":900,"time":36},"check":"second regression","expected":{"distance":0,"fare":750,"time":36},"passed":false},{"actual":{"distance":1764,"fare":2059,"time":45},"check":"normal control 1","expected":{"distance":1764,"fare":2059,"time":45},"passed":true},{"actual":{"distance":125,"fare":700,"time":71},"check":"normal control 2","expected":{"distance":125,"fare":700,"time":71},"passed":true},{"actual":{"distance":0,"fare":1000,"time":36},"check":"normal control 3","expected":{"distance":0,"fare":1000,"time":36},"passed":true},{"actual":{"distance":1706,"fare":2237,"time":31},"check":"normal control 4","expected":{"distance":1706,"fare":2237,"time":31},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: base inside minimum\", \"actual\": {\"distance\": 0, \"time\": 679, \"fare\": 1500}, \"expected\": {\"distance\": 0, \"fare\": 1250, \"time\": 679}, \"passed\": false}, {\"check\": \"partial repair probe: base inside minimum\", \"actual\": {\"distance\": 238, \"time\": 0, \"fare\": 1100}, \"expected\": {\"distance\": 238, \"fare\": 950, \"time\": 0}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"distance\": 0, \"time\": 36, \"fare\": 900}, \"expected\": {\"distance\": 0, \"fare\": 750, \"time\": 36}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"distance\": 1764, \"time\": 45, \"fare\": 2059}, \"expected\": {\"distance\": 1764, \"fare\": 2059, \"time\": 45}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"distance\": 125, \"time\": 71, \"fare\": 700}, \"expected\": {\"distance\": 125, \"fare\": 700, \"time\": 71}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"distance\": 0, \"time\": 36, \"fare\": 1000}, \"expected\": {\"distance\": 0, \"fare\": 1000, \"time\": 36}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"distance\": 1706, \"time\": 31, \"fare\": 2237}, \"expected\": {\"distance\": 1706, \"fare\": 2237, \"time\": 31}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.735,"exit_code":1,"observations":[{"actual":{"distance":0,"fare":1500,"time":679},"check":"regression: base inside minimum","expected":{"distance":0,"fare":1250,"time":679},"passed":false},{"actual":{"distance":238,"fare":1100,"time":0},"check":"partial repair probe: base inside minimum","expected":{"distance":238,"fare":950,"time":0},"passed":false},{"actual":{"distance":0,"fare":900,"time":36},"check":"second regression","expected":{"distance":0,"fare":750,"time":36},"passed":false},{"actual":{"distance":1764,"fare":2059,"time":45},"check":"normal control 1","expected":{"distance":1764,"fare":2059,"time":45},"passed":true},{"actual":{"distance":125,"fare":700,"time":71},"check":"normal control 2","expected":{"distance":125,"fare":700,"time":71},"passed":true},{"actual":{"distance":0,"fare":1000,"time":36},"check":"normal control 3","expected":{"distance":0,"fare":1000,"time":36},"passed":true},{"actual":{"distance":1706,"fare":2237,"time":31},"check":"normal control 4","expected":{"distance":1706,"fare":2237,"time":31},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: base inside minimum\", \"actual\": {\"distance\": 0, \"time\": 679, \"fare\": 1500}, \"expected\": {\"distance\": 0, \"fare\": 1250, \"time\": 679}, \"passed\": false}, {\"check\": \"partial repair probe: base inside minimum\", \"actual\": {\"distance\": 238, \"time\": 0, \"fare\": 1100}, \"expected\": {\"distance\": 238, \"fare\": 950, \"time\": 0}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"distance\": 0, \"time\": 36, \"fare\": 900}, \"expected\": {\"distance\": 0, \"fare\": 750, \"time\": 36}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"distance\": 1764, \"time\": 45, \"fare\": 2059}, \"expected\": {\"distance\": 1764, \"fare\": 2059, \"time\": 45}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"distance\": 125, \"time\": 71, \"fare\": 700}, \"expected\": {\"distance\": 125, \"fare\": 700, \"time\": 71}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"distance\": 0, \"time\": 36, \"fare\": 1000}, \"expected\": {\"distance\": 0, \"fare\": 1000, \"time\": 36}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"distance\": 1706, \"time\": 31, \"fare\": 2237}, \"expected\": {\"distance\": 1706, \"fare\": 2237, \"time\": 31}, \"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."}}