{"abstract":"Final fares land above the displayed range more often than expected.","category":"Ride-hailing fare and surge pricing","checks":7,"contract":"Show a fare range from a point estimate in cents: low = 90% of the estimate floored to whole dollars, but never below the minimum fare; high = 110% of the estimate rounded up to whole dollars; if the range is narrower than 2.00 the high end becomes low + 2.00. Return [low, high] cents.","contract_signature":"est, minimum","evaluation_group":"w2-ride-hailing-fare-surge-estimate-range","failed_approach":"Rounding to the nearest dollar still undershoots 110%.","family":"w2-ride-hailing-fare-surge-estimate-range-high-end-ceiling","id":"FA-85686","implementations":{"attempt":{"sha256":"e5560089c72651392d8840345f960a892b9bee6c567e60f13905bceb74b9c1fd","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(est, minimum):\n    low = max(est * 9 // 10 // 100 * 100, minimum)\n    high = (est * 11 + 500) // 1000 * 100\n    if high - low < 200:\n        high = low + 200\n    return [low, high]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: high end ceiling', [2500, 1000], [2200, 2800]),\n  ('partial repair probe: high end ceiling', [1111, 1000], [1000, 1300]),\n  ('second regression', [2050, 500], [1800, 2300]), ('normal control 1', [1000, 500], [900, 1100]),\n  ('normal control 2', [1000, 800], [900, 1100]), ('normal control 3', [1064, 1000], [1000, 1200]),\n  ('normal control 4', [700, 800], [800, 1000])],\n [('regression: high end ceiling', [1111, 800], [900, 1300]),\n  ('partial repair probe: high end ceiling', [2669, 500], [2400, 3000]),\n  ('second regression', [2050, 1000], [1800, 2300]), ('normal control 1', [1000, 500], [900, 1100]),\n  ('normal control 2', [700, 800], [800, 1000]), ('normal control 3', [1000, 800], [900, 1100]),\n  ('normal control 4', [700, 500], [600, 800])],\n [('regression: high end ceiling', [1111, 500], [900, 1300]),\n  ('partial repair probe: high end ceiling', [1111, 1000], [1000, 1300]),\n  ('second regression', [1234, 500], [1100, 1400]), ('normal control 1', [700, 800], [800, 1000]),\n  ('normal control 2', [995, 1000], [1000, 1200]), ('normal control 3', [1000, 800], [900, 1100]),\n  ('normal control 4', [700, 1000], [1000, 1200])],\n [('regression: high end ceiling', [4125, 800], [3700, 4600]),\n  ('partial repair probe: high end ceiling', [1111, 500], [900, 1300]),\n  ('second regression', [3137, 500], [2800, 3500]), ('normal control 1', [700, 500], [600, 800]),\n  ('normal control 2', [700, 800], [800, 1000]), ('normal control 3', [1000, 1000], [1000, 1200]),\n  ('normal control 4', [1000, 500], [900, 1100])],\n [('regression: high end ceiling', [1999, 500], [1700, 2200]),\n  ('partial repair probe: high end ceiling', [1284, 500], [1100, 1500]),\n  ('second regression', [1999, 1000], [1700, 2200]), ('normal control 1', [1000, 1000], [1000, 1200]),\n  ('normal control 2', [1000, 800], [900, 1100]), ('normal control 3', [700, 500], [600, 800]),\n  ('normal control 4', [1000, 500], [900, 1100])]]\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":"d5c89dac228230b5fbfcff5b2817f7acd99c177f927e25a4a475d3049cbd5c9d","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(est, minimum):\n    low = max(est * 9 // 10 // 100 * 100, minimum)\n    high = est * 11 // 1000 * 100\n    if high - low < 200:\n        high = low + 200\n    return [low, high]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: high end ceiling', [2500, 1000], [2200, 2800]),\n  ('partial repair probe: high end ceiling', [1111, 1000], [1000, 1300]),\n  ('second regression', [2050, 500], [1800, 2300]), ('normal control 1', [1000, 500], [900, 1100]),\n  ('normal control 2', [1000, 800], [900, 1100]), ('normal control 3', [1064, 1000], [1000, 1200]),\n  ('normal control 4', [700, 800], [800, 1000])],\n [('regression: high end ceiling', [1111, 800], [900, 1300]),\n  ('partial repair probe: high end ceiling', [2669, 500], [2400, 3000]),\n  ('second regression', [2050, 1000], [1800, 2300]), ('normal control 1', [1000, 500], [900, 1100]),\n  ('normal control 2', [700, 800], [800, 1000]), ('normal control 3', [1000, 800], [900, 1100]),\n  ('normal control 4', [700, 500], [600, 800])],\n [('regression: high end ceiling', [1111, 500], [900, 1300]),\n  ('partial repair probe: high end ceiling', [1111, 1000], [1000, 1300]),\n  ('second regression', [1234, 500], [1100, 1400]), ('normal control 1', [700, 800], [800, 1000]),\n  ('normal control 2', [995, 1000], [1000, 1200]), ('normal control 3', [1000, 800], [900, 1100]),\n  ('normal control 4', [700, 1000], [1000, 1200])],\n [('regression: high end ceiling', [4125, 800], [3700, 4600]),\n  ('partial repair probe: high end ceiling', [1111, 500], [900, 1300]),\n  ('second regression', [3137, 500], [2800, 3500]), ('normal control 1', [700, 500], [600, 800]),\n  ('normal control 2', [700, 800], [800, 1000]), ('normal control 3', [1000, 1000], [1000, 1200]),\n  ('normal control 4', [1000, 500], [900, 1100])],\n [('regression: high end ceiling', [1999, 500], [1700, 2200]),\n  ('partial repair probe: high end ceiling', [1284, 500], [1100, 1500]),\n  ('second regression', [1999, 1000], [1700, 2200]), ('normal control 1', [1000, 1000], [1000, 1200]),\n  ('normal control 2', [1000, 800], [900, 1100]), ('normal control 3', [700, 500], [600, 800]),\n  ('normal control 4', [1000, 500], [900, 1100])]]\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-estimate-range-high-end-ceiling","generated_at":"2026-09-29T14:50:42.616400+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 high bound floors instead of rounding up.","sha256":"711ba41c3543144ec2ec2e53f2910c12a94623e368fede696c33725fa2c44d42","title":"High estimate floored below 110% · 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":38.783,"exit_code":1,"observations":[{"actual":[2200,2800],"check":"regression: high end ceiling","expected":[2200,2800],"passed":true},{"actual":[1000,1200],"check":"partial repair probe: high end ceiling","expected":[1000,1300],"passed":false},{"actual":[1800,2300],"check":"second regression","expected":[1800,2300],"passed":true},{"actual":[900,1100],"check":"normal control 1","expected":[900,1100],"passed":true},{"actual":[900,1100],"check":"normal control 2","expected":[900,1100],"passed":true},{"actual":[1000,1200],"check":"normal control 3","expected":[1000,1200],"passed":true},{"actual":[800,1000],"check":"normal control 4","expected":[800,1000],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: high end ceiling\", \"actual\": [2200, 2800], \"expected\": [2200, 2800], \"passed\": true}, {\"check\": \"partial repair probe: high end ceiling\", \"actual\": [1000, 1200], \"expected\": [1000, 1300], \"passed\": false}, {\"check\": \"second regression\", \"actual\": [1800, 2300], \"expected\": [1800, 2300], \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": [900, 1100], \"expected\": [900, 1100], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [900, 1100], \"expected\": [900, 1100], \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": [1000, 1200], \"expected\": [1000, 1200], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [800, 1000], \"expected\": [800, 1000], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.1,"exit_code":1,"observations":[{"actual":[2200,2700],"check":"regression: high end ceiling","expected":[2200,2800],"passed":false},{"actual":[1000,1200],"check":"partial repair probe: high end ceiling","expected":[1000,1300],"passed":false},{"actual":[1800,2200],"check":"second regression","expected":[1800,2300],"passed":false},{"actual":[900,1100],"check":"normal control 1","expected":[900,1100],"passed":true},{"actual":[900,1100],"check":"normal control 2","expected":[900,1100],"passed":true},{"actual":[1000,1200],"check":"normal control 3","expected":[1000,1200],"passed":true},{"actual":[800,1000],"check":"normal control 4","expected":[800,1000],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: high end ceiling\", \"actual\": [2200, 2700], \"expected\": [2200, 2800], \"passed\": false}, {\"check\": \"partial repair probe: high end ceiling\", \"actual\": [1000, 1200], \"expected\": [1000, 1300], \"passed\": false}, {\"check\": \"second regression\", \"actual\": [1800, 2200], \"expected\": [1800, 2300], \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": [900, 1100], \"expected\": [900, 1100], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [900, 1100], \"expected\": [900, 1100], \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": [1000, 1200], \"expected\": [1000, 1200], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [800, 1000], \"expected\": [800, 1000], \"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."}}