{"abstract":"When only one rider meets the overlap threshold, that rider still receives the matched discount.","category":"Ride-hailing fare and surge pricing","checks":7,"contract":"In a shared ride, a rider counts as matched if they shared at least min_overlap_s seconds with another rider; a match needs at least two such riders, otherwise nobody is matched. Matched riders pay solo x (100 - discount_pct)% and unmatched riders pay solo x 95%, both floored to the cent in the rider's favor. Return id -> price.","contract_signature":"riders, discount_pct, min_overlap_s","evaluation_group":"w2-ride-hailing-fare-surge-shared-ride-discount","failed_approach":"Counting all riders instead of qualifying riders still leaves a lone qualifier matched.","family":"w2-ride-hailing-fare-surge-shared-ride-discount-lone-matched-rider","id":"FA-85546","implementations":{"attempt":{"sha256":"3db611d20bb30d34fbaab9fced7962e23d2d544c1a6351dfabc3031b355ebde6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(riders, discount_pct, min_overlap_s):\n    matched = [r['id'] for r in riders if r['overlap_s'] >= min_overlap_s]\n    if len(riders) < 2:\n        matched = []\n    out = {}\n    for r in riders:\n        pct = discount_pct if r['id'] in matched else 5\n        out[r['id']] = r['solo'] * (100 - pct) // 100\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1999}, {'id': 'r1', 'overlap_s': 0, 'solo': 1999},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 1999}],\n    25, 180],\n   {'r0': 1899, 'r1': 1899, 'r2': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 2505}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 877}],\n    25, 180],\n   {'r0': 2379, 'r1': 833, 'r2': 833}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 180, 'solo': 1999}], 30, 180], {'r0': 1899}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 0, 'solo': 2505}, {'id': 'r1', 'overlap_s': 179, 'solo': 1234}], 40, 180],\n   {'r0': 2379, 'r1': 1172}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 0, 'solo': 2505}, {'id': 'r3', 'overlap_s': 600, 'solo': 1234}],\n    25, 180],\n   {'r0': 1878, 'r1': 1878, 'r2': 2379, 'r3': 925}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 181, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 181, 'solo': 1999}],\n    40, 180],\n   {'r0': 1899, 'r1': 526, 'r2': 1199}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 877}, {'id': 'r1', 'overlap_s': 181, 'solo': 1234}], 30, 180],\n   {'r0': 613, 'r1': 863})],\n [('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 600, 'solo': 1999}], 25, 180],\n   {'r0': 1899, 'r1': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 600, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 1234}, {'id': 'r3', 'overlap_s': 0, 'solo': 877}],\n    30, 180],\n   {'r0': 1899, 'r1': 2379, 'r2': 1172, 'r3': 833}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 30, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 877}, {'id': 'r1', 'overlap_s': 3, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 877}, {'id': 'r3', 'overlap_s': 600, 'solo': 1234}],\n    40, 180],\n   {'r0': 526, 'r1': 833, 'r2': 833, 'r3': 740}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 180, 'solo': 1999}],\n    25, 180],\n   {'r0': 925, 'r1': 657, 'r2': 1499}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 877}, {'id': 'r1', 'overlap_s': 3, 'solo': 877}], 25, 180],\n   {'r0': 833, 'r1': 833}),\n  ('normal control 4', [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}], 40, 180], {'r0': 1899})],\n [('regression: lone matched rider', [[{'id': 'r0', 'overlap_s': 180, 'solo': 877}], 30, 180], {'r0': 833}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 2505}, {'id': 'r1', 'overlap_s': 3, 'solo': 2505}], 30, 180],\n   {'r0': 2379, 'r1': 2379}),\n  ('second regression',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 1234}, {'id': 'r1', 'overlap_s': 181, 'solo': 1999}], 30, 180],\n   {'r0': 1172, 'r1': 1899}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 1999}, {'id': 'r1', 'overlap_s': 179, 'solo': 1999}], 40, 180],\n   {'r0': 1899, 'r1': 1899}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 877}], 25, 180],\n   {'r0': 1878, 'r1': 657}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 600, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 2505}, {'id': 'r3', 'overlap_s': 180, 'solo': 877}],\n    25, 180],\n   {'r0': 925, 'r1': 1878, 'r2': 1878, 'r3': 657}),\n  ('normal control 4', [[{'id': 'r0', 'overlap_s': 3, 'solo': 1234}], 30, 180], {'r0': 1172})],\n [('regression: lone matched rider', [[{'id': 'r0', 'overlap_s': 600, 'solo': 1999}], 30, 180], {'r0': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 1234}, {'id': 'r1', 'overlap_s': 3, 'solo': 2505}], 25, 180],\n   {'r0': 1172, 'r1': 2379}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 25, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 877}, {'id': 'r1', 'overlap_s': 181, 'solo': 877}], 25, 180],\n   {'r0': 657, 'r1': 657}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 1999}, {'id': 'r3', 'overlap_s': 0, 'solo': 1234}],\n    25, 180],\n   {'r0': 925, 'r1': 1878, 'r2': 1499, 'r3': 1172}),\n  ('normal control 3', [[{'id': 'r0', 'overlap_s': 0, 'solo': 877}], 40, 180], {'r0': 833}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 2505}],\n    40, 180],\n   {'r0': 740, 'r1': 526, 'r2': 2379})],\n [('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 179, 'solo': 1999}], 25, 180],\n   {'r0': 1172, 'r1': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 877}, {'id': 'r1', 'overlap_s': 179, 'solo': 1234},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 2505}],\n    30, 180],\n   {'r0': 833, 'r1': 1172, 'r2': 2379}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 40, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 877}, {'id': 'r1', 'overlap_s': 180, 'solo': 1234},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 877}],\n    25, 180],\n   {'r0': 657, 'r1': 925, 'r2': 657}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 1234}], 25, 180],\n   {'r0': 1878, 'r1': 925}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 179, 'solo': 2505}], 25, 180],\n   {'r0': 1899, 'r1': 2379}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 877}, {'id': 'r1', 'overlap_s': 0, 'solo': 1999}], 25, 180],\n   {'r0': 833, 'r1': 1899})]]\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":"5e63ccbcd794dedc12d8755112b32e67770658b301c6b04d8a4227606c0904fe","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(riders, discount_pct, min_overlap_s):\n    matched = [r['id'] for r in riders if r['overlap_s'] >= min_overlap_s]\n    out = {}\n    for r in riders:\n        pct = discount_pct if r['id'] in matched else 5\n        out[r['id']] = r['solo'] * (100 - pct) // 100\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1999}, {'id': 'r1', 'overlap_s': 0, 'solo': 1999},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 1999}],\n    25, 180],\n   {'r0': 1899, 'r1': 1899, 'r2': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 2505}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 877}],\n    25, 180],\n   {'r0': 2379, 'r1': 833, 'r2': 833}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 180, 'solo': 1999}], 30, 180], {'r0': 1899}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 0, 'solo': 2505}, {'id': 'r1', 'overlap_s': 179, 'solo': 1234}], 40, 180],\n   {'r0': 2379, 'r1': 1172}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 0, 'solo': 2505}, {'id': 'r3', 'overlap_s': 600, 'solo': 1234}],\n    25, 180],\n   {'r0': 1878, 'r1': 1878, 'r2': 2379, 'r3': 925}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 181, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 181, 'solo': 1999}],\n    40, 180],\n   {'r0': 1899, 'r1': 526, 'r2': 1199}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 877}, {'id': 'r1', 'overlap_s': 181, 'solo': 1234}], 30, 180],\n   {'r0': 613, 'r1': 863})],\n [('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 600, 'solo': 1999}], 25, 180],\n   {'r0': 1899, 'r1': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 600, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 3, 'solo': 1234}, {'id': 'r3', 'overlap_s': 0, 'solo': 877}],\n    30, 180],\n   {'r0': 1899, 'r1': 2379, 'r2': 1172, 'r3': 833}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 30, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 877}, {'id': 'r1', 'overlap_s': 3, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 877}, {'id': 'r3', 'overlap_s': 600, 'solo': 1234}],\n    40, 180],\n   {'r0': 526, 'r1': 833, 'r2': 833, 'r3': 740}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 180, 'solo': 1999}],\n    25, 180],\n   {'r0': 925, 'r1': 657, 'r2': 1499}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 877}, {'id': 'r1', 'overlap_s': 3, 'solo': 877}], 25, 180],\n   {'r0': 833, 'r1': 833}),\n  ('normal control 4', [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}], 40, 180], {'r0': 1899})],\n [('regression: lone matched rider', [[{'id': 'r0', 'overlap_s': 180, 'solo': 877}], 30, 180], {'r0': 833}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 2505}, {'id': 'r1', 'overlap_s': 3, 'solo': 2505}], 30, 180],\n   {'r0': 2379, 'r1': 2379}),\n  ('second regression',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 1234}, {'id': 'r1', 'overlap_s': 181, 'solo': 1999}], 30, 180],\n   {'r0': 1172, 'r1': 1899}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 3, 'solo': 1999}, {'id': 'r1', 'overlap_s': 179, 'solo': 1999}], 40, 180],\n   {'r0': 1899, 'r1': 1899}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 877}], 25, 180],\n   {'r0': 1878, 'r1': 657}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 600, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 2505}, {'id': 'r3', 'overlap_s': 180, 'solo': 877}],\n    25, 180],\n   {'r0': 925, 'r1': 1878, 'r2': 1878, 'r3': 657}),\n  ('normal control 4', [[{'id': 'r0', 'overlap_s': 3, 'solo': 1234}], 30, 180], {'r0': 1172})],\n [('regression: lone matched rider', [[{'id': 'r0', 'overlap_s': 600, 'solo': 1999}], 30, 180], {'r0': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 1234}, {'id': 'r1', 'overlap_s': 3, 'solo': 2505}], 25, 180],\n   {'r0': 1172, 'r1': 2379}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 25, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 877}, {'id': 'r1', 'overlap_s': 181, 'solo': 877}], 25, 180],\n   {'r0': 657, 'r1': 657}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 2505},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 1999}, {'id': 'r3', 'overlap_s': 0, 'solo': 1234}],\n    25, 180],\n   {'r0': 925, 'r1': 1878, 'r2': 1499, 'r3': 1172}),\n  ('normal control 3', [[{'id': 'r0', 'overlap_s': 0, 'solo': 877}], 40, 180], {'r0': 833}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 1234}, {'id': 'r1', 'overlap_s': 180, 'solo': 877},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 2505}],\n    40, 180],\n   {'r0': 740, 'r1': 526, 'r2': 2379})],\n [('regression: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 180, 'solo': 1234}, {'id': 'r1', 'overlap_s': 179, 'solo': 1999}], 25, 180],\n   {'r0': 1172, 'r1': 1899}),\n  ('partial repair probe: lone matched rider',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 877}, {'id': 'r1', 'overlap_s': 179, 'solo': 1234},\n     {'id': 'r2', 'overlap_s': 179, 'solo': 2505}],\n    30, 180],\n   {'r0': 833, 'r1': 1172, 'r2': 2379}),\n  ('second regression', [[{'id': 'r0', 'overlap_s': 181, 'solo': 1234}], 40, 180], {'r0': 1172}),\n  ('normal control 1',\n   [[{'id': 'r0', 'overlap_s': 600, 'solo': 877}, {'id': 'r1', 'overlap_s': 180, 'solo': 1234},\n     {'id': 'r2', 'overlap_s': 600, 'solo': 877}],\n    25, 180],\n   {'r0': 657, 'r1': 925, 'r2': 657}),\n  ('normal control 2',\n   [[{'id': 'r0', 'overlap_s': 181, 'solo': 2505}, {'id': 'r1', 'overlap_s': 181, 'solo': 1234}], 25, 180],\n   {'r0': 1878, 'r1': 925}),\n  ('normal control 3',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 1999}, {'id': 'r1', 'overlap_s': 179, 'solo': 2505}], 25, 180],\n   {'r0': 1899, 'r1': 2379}),\n  ('normal control 4',\n   [[{'id': 'r0', 'overlap_s': 179, 'solo': 877}, {'id': 'r1', 'overlap_s': 0, 'solo': 1999}], 25, 180],\n   {'r0': 833, 'r1': 1899})]]\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-shared-ride-discount-lone-matched-rider","generated_at":"2026-09-29T14:50:41.325524+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 two-rider requirement for a match is missing.","sha256":"184cf0a5822cc9c6bf350bc3a19ef01b12ccf284819d8d266d7f04e51abefdeb","title":"A single rider with overlap gets the shared discount · 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":42.198,"exit_code":1,"observations":[{"actual":{"r0":1499,"r1":1899,"r2":1899},"check":"regression: lone matched rider","expected":{"r0":1899,"r1":1899,"r2":1899},"passed":false},{"actual":{"r0":2379,"r1":657,"r2":833},"check":"partial repair probe: lone matched rider","expected":{"r0":2379,"r1":833,"r2":833},"passed":false},{"actual":{"r0":1899},"check":"second regression","expected":{"r0":1899},"passed":true},{"actual":{"r0":2379,"r1":1172},"check":"normal control 1","expected":{"r0":2379,"r1":1172},"passed":true},{"actual":{"r0":1878,"r1":1878,"r2":2379,"r3":925},"check":"normal control 2","expected":{"r0":1878,"r1":1878,"r2":2379,"r3":925},"passed":true},{"actual":{"r0":1899,"r1":526,"r2":1199},"check":"normal control 3","expected":{"r0":1899,"r1":526,"r2":1199},"passed":true},{"actual":{"r0":613,"r1":863},"check":"normal control 4","expected":{"r0":613,"r1":863},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: lone matched rider\", \"actual\": {\"r0\": 1499, \"r1\": 1899, \"r2\": 1899}, \"expected\": {\"r0\": 1899, \"r1\": 1899, \"r2\": 1899}, \"passed\": false}, {\"check\": \"partial repair probe: lone matched rider\", \"actual\": {\"r0\": 2379, \"r1\": 657, \"r2\": 833}, \"expected\": {\"r0\": 2379, \"r1\": 833, \"r2\": 833}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"r0\": 1899}, \"expected\": {\"r0\": 1899}, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": {\"r0\": 2379, \"r1\": 1172}, \"expected\": {\"r0\": 2379, \"r1\": 1172}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"r0\": 1878, \"r1\": 1878, \"r2\": 2379, \"r3\": 925}, \"expected\": {\"r0\": 1878, \"r1\": 1878, \"r2\": 2379, \"r3\": 925}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"r0\": 1899, \"r1\": 526, \"r2\": 1199}, \"expected\": {\"r0\": 1899, \"r1\": 526, \"r2\": 1199}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"r0\": 613, \"r1\": 863}, \"expected\": {\"r0\": 613, \"r1\": 863}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.752,"exit_code":1,"observations":[{"actual":{"r0":1499,"r1":1899,"r2":1899},"check":"regression: lone matched rider","expected":{"r0":1899,"r1":1899,"r2":1899},"passed":false},{"actual":{"r0":2379,"r1":657,"r2":833},"check":"partial repair probe: lone matched rider","expected":{"r0":2379,"r1":833,"r2":833},"passed":false},{"actual":{"r0":1399},"check":"second regression","expected":{"r0":1899},"passed":false},{"actual":{"r0":2379,"r1":1172},"check":"normal control 1","expected":{"r0":2379,"r1":1172},"passed":true},{"actual":{"r0":1878,"r1":1878,"r2":2379,"r3":925},"check":"normal control 2","expected":{"r0":1878,"r1":1878,"r2":2379,"r3":925},"passed":true},{"actual":{"r0":1899,"r1":526,"r2":1199},"check":"normal control 3","expected":{"r0":1899,"r1":526,"r2":1199},"passed":true},{"actual":{"r0":613,"r1":863},"check":"normal control 4","expected":{"r0":613,"r1":863},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: lone matched rider\", \"actual\": {\"r0\": 1499, \"r1\": 1899, \"r2\": 1899}, \"expected\": {\"r0\": 1899, \"r1\": 1899, \"r2\": 1899}, \"passed\": false}, {\"check\": \"partial repair probe: lone matched rider\", \"actual\": {\"r0\": 2379, \"r1\": 657, \"r2\": 833}, \"expected\": {\"r0\": 2379, \"r1\": 833, \"r2\": 833}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"r0\": 1399}, \"expected\": {\"r0\": 1899}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"r0\": 2379, \"r1\": 1172}, \"expected\": {\"r0\": 2379, \"r1\": 1172}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"r0\": 1878, \"r1\": 1878, \"r2\": 2379, \"r3\": 925}, \"expected\": {\"r0\": 1878, \"r1\": 1878, \"r2\": 2379, \"r3\": 925}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"r0\": 1899, \"r1\": 526, \"r2\": 1199}, \"expected\": {\"r0\": 1899, \"r1\": 526, \"r2\": 1199}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"r0\": 613, \"r1\": 863}, \"expected\": {\"r0\": 613, \"r1\": 863}, \"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."}}