{"abstract":"Modified following behaves like plain following at month end.","category":"Bond day-count conventions","checks":8,"contract":"Inputs a date [y,m,d], a convention code and a list of holiday dates. Saturdays, Sundays and holidays are non-business days. F rolls forward, P rolls back, MF rolls forward unless that changes the month in which case it rolls back, MP rolls back unless that changes the month in which case it rolls forward, U leaves the date unadjusted; other codes return \"unknown convention\". Return the adjusted [y,m,d].","evaluation_group":"w2-bond_day_count_conventions-business-day-adjustment","failed_approach":"Stepping back exactly one calendar day from the original date can land on another non-business day.","family":"w2-bond_day_count_conventions-business-day-adjustment-modified-following-fallback","id":"FA-60986","implementations":{"attempt":{"sha256":"1f8bbd021c6b5f0eeecacc0e2a2b945eca854dd1ee2de6fd496246605acc77c5","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(d, conv, holidays):\n    D = datetime.date(*d)\n    H = {datetime.date(*h) for h in holidays}\n    def bad(x):\n        return x.weekday() >= 5 or x in H\n    def roll(x, step):\n        while bad(x):\n            x += datetime.timedelta(days=step)\n        return x\n    if conv == 'F':\n        r = roll(D, 1)\n    elif conv == 'MF':\n        r = roll(D, 1)\n        if r.month != D.month:\n            r = D - datetime.timedelta(days=1)\n    elif conv == 'P':\n        r = roll(D, -1)\n    elif conv == 'MP':\n        r = roll(D, -1)\n        if r.month != D.month:\n            r = roll(D, 1)\n    elif conv == 'U':\n        r = D\n    else:\n        return 'unknown convention'\n    return [r.year, r.month, r.day]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression modified following fallback 1', [[2027, 12, 31], 'MF', [[2027, 12, 31]]], [2027, 12, 30]], ['regression modified following fallback 2', [[2025, 8, 30], 'MF', [[2025, 9, 2], [2025, 8, 31]]], [2025, 8, 29]], ['partial repair probe 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2024, 1, 4], [2023, 12, 29]]], [2023, 12, 28]], ['boundary control 1', [[2024, 5, 15], 'X', []], 'unknown convention'], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2030, 12, 21], 'F', [[2030, 12, 18], [2030, 12, 20], [2030, 12, 18]]], [2030, 12, 23]], ['normal control 2', [[2024, 7, 31], 'MP', [[2024, 8, 2], [2024, 7, 29]]], [2024, 7, 31]]], [['regression modified following fallback 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['regression modified following fallback 2', [[2026, 2, 28], 'MF', []], [2026, 2, 27]], ['partial repair probe 1', [[2023, 4, 30], 'MF', [[2023, 4, 29], [2023, 5, 1]]], [2023, 4, 28]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2023, 12, 31]]], [2023, 12, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['normal control 1', [[2023, 11, 4], 'F', []], [2023, 11, 6]], ['normal control 2', [[2025, 9, 1], 'X', [[2025, 9, 4]]], 'unknown convention']], [['regression modified following fallback 1', [[2030, 3, 31], 'MF', [[2030, 3, 28], [2030, 4, 4]]], [2030, 3, 29]], ['regression modified following fallback 2', [[2024, 8, 29], 'MF', [[2024, 8, 30], [2024, 8, 29]]], [2024, 8, 28]], ['partial repair probe 1', [[2024, 6, 29], 'MF', [[2024, 7, 2], [2024, 6, 28]]], [2024, 6, 27]], ['partial repair probe 2', [[2028, 12, 31], 'MF', [[2028, 12, 29], [2029, 1, 1]]], [2028, 12, 28]], ['boundary control 1', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2026, 1, 18], 'MP', [[2026, 1, 21]]], [2026, 1, 16]], ['normal control 2', [[2020, 6, 1], 'MP', [[2020, 5, 30], [2020, 6, 5], [2020, 5, 30]]], [2020, 6, 1]]], [['regression modified following fallback 1', [[2020, 5, 31], 'MF', []], [2020, 5, 29]], ['regression modified following fallback 2', [[2022, 12, 31], 'MF', []], [2022, 12, 30]], ['partial repair probe 1', [[2021, 10, 31], 'MF', []], [2021, 10, 29]], ['partial repair probe 2', [[2019, 3, 31], 'MF', [[2019, 3, 30]]], [2019, 3, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2028, 4, 30], 'P', []], [2028, 4, 28]], ['normal control 2', [[2028, 11, 30], 'X', []], 'unknown convention']], [['regression modified following fallback 1', [[2025, 12, 31], 'MF', [[2025, 12, 31]]], [2025, 12, 30]], ['regression modified following fallback 2', [[2027, 1, 31], 'MF', []], [2027, 1, 29]], ['partial repair probe 1', [[2024, 3, 31], 'MF', [[2024, 3, 30]]], [2024, 3, 29]], ['partial repair probe 2', [[2028, 12, 31], 'MF', []], [2028, 12, 29]], ['boundary control 1', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2023, 3, 29], 'MP', [[2023, 3, 28], [2023, 3, 31]]], [2023, 3, 29]], ['normal control 2', [[2026, 10, 1], 'MP', []], [2026, 10, 1]]]]\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":"8210aac703efad7c74c19ae6446902770358c8060219ebc67f2064e68c6ad8dc","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(d, conv, holidays):\n    D = datetime.date(*d)\n    H = {datetime.date(*h) for h in holidays}\n    def bad(x):\n        return x.weekday() >= 5 or x in H\n    def roll(x, step):\n        while bad(x):\n            x += datetime.timedelta(days=step)\n        return x\n    if conv == 'F':\n        r = roll(D, 1)\n    elif conv == 'MF':\n        r = roll(D, 1)\n        if r.month != D.month:\n            r = roll(r, -1)\n    elif conv == 'P':\n        r = roll(D, -1)\n    elif conv == 'MP':\n        r = roll(D, -1)\n        if r.month != D.month:\n            r = roll(D, 1)\n    elif conv == 'U':\n        r = D\n    else:\n        return 'unknown convention'\n    return [r.year, r.month, r.day]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression modified following fallback 1', [[2027, 12, 31], 'MF', [[2027, 12, 31]]], [2027, 12, 30]], ['regression modified following fallback 2', [[2025, 8, 30], 'MF', [[2025, 9, 2], [2025, 8, 31]]], [2025, 8, 29]], ['partial repair probe 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2024, 1, 4], [2023, 12, 29]]], [2023, 12, 28]], ['boundary control 1', [[2024, 5, 15], 'X', []], 'unknown convention'], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2030, 12, 21], 'F', [[2030, 12, 18], [2030, 12, 20], [2030, 12, 18]]], [2030, 12, 23]], ['normal control 2', [[2024, 7, 31], 'MP', [[2024, 8, 2], [2024, 7, 29]]], [2024, 7, 31]]], [['regression modified following fallback 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['regression modified following fallback 2', [[2026, 2, 28], 'MF', []], [2026, 2, 27]], ['partial repair probe 1', [[2023, 4, 30], 'MF', [[2023, 4, 29], [2023, 5, 1]]], [2023, 4, 28]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2023, 12, 31]]], [2023, 12, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['normal control 1', [[2023, 11, 4], 'F', []], [2023, 11, 6]], ['normal control 2', [[2025, 9, 1], 'X', [[2025, 9, 4]]], 'unknown convention']], [['regression modified following fallback 1', [[2030, 3, 31], 'MF', [[2030, 3, 28], [2030, 4, 4]]], [2030, 3, 29]], ['regression modified following fallback 2', [[2024, 8, 29], 'MF', [[2024, 8, 30], [2024, 8, 29]]], [2024, 8, 28]], ['partial repair probe 1', [[2024, 6, 29], 'MF', [[2024, 7, 2], [2024, 6, 28]]], [2024, 6, 27]], ['partial repair probe 2', [[2028, 12, 31], 'MF', [[2028, 12, 29], [2029, 1, 1]]], [2028, 12, 28]], ['boundary control 1', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2026, 1, 18], 'MP', [[2026, 1, 21]]], [2026, 1, 16]], ['normal control 2', [[2020, 6, 1], 'MP', [[2020, 5, 30], [2020, 6, 5], [2020, 5, 30]]], [2020, 6, 1]]], [['regression modified following fallback 1', [[2020, 5, 31], 'MF', []], [2020, 5, 29]], ['regression modified following fallback 2', [[2022, 12, 31], 'MF', []], [2022, 12, 30]], ['partial repair probe 1', [[2021, 10, 31], 'MF', []], [2021, 10, 29]], ['partial repair probe 2', [[2019, 3, 31], 'MF', [[2019, 3, 30]]], [2019, 3, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2028, 4, 30], 'P', []], [2028, 4, 28]], ['normal control 2', [[2028, 11, 30], 'X', []], 'unknown convention']], [['regression modified following fallback 1', [[2025, 12, 31], 'MF', [[2025, 12, 31]]], [2025, 12, 30]], ['regression modified following fallback 2', [[2027, 1, 31], 'MF', []], [2027, 1, 29]], ['partial repair probe 1', [[2024, 3, 31], 'MF', [[2024, 3, 30]]], [2024, 3, 29]], ['partial repair probe 2', [[2028, 12, 31], 'MF', []], [2028, 12, 29]], ['boundary control 1', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2023, 3, 29], 'MP', [[2023, 3, 28], [2023, 3, 31]]], [2023, 3, 29]], ['normal control 2', [[2026, 10, 1], 'MP', []], [2026, 10, 1]]]]\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":"8dbf135f7126be5f3ac832bb130de8cc2b8bde5632e459af2249d3f98ac506aa","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(d, conv, holidays):\n    D = datetime.date(*d)\n    H = {datetime.date(*h) for h in holidays}\n    def bad(x):\n        return x.weekday() >= 5 or x in H\n    def roll(x, step):\n        while bad(x):\n            x += datetime.timedelta(days=step)\n        return x\n    if conv == 'F':\n        r = roll(D, 1)\n    elif conv == 'MF':\n        r = roll(D, 1)\n        if r.month != D.month:\n            r = roll(D, -1)\n    elif conv == 'P':\n        r = roll(D, -1)\n    elif conv == 'MP':\n        r = roll(D, -1)\n        if r.month != D.month:\n            r = roll(D, 1)\n    elif conv == 'U':\n        r = D\n    else:\n        return 'unknown convention'\n    return [r.year, r.month, r.day]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression modified following fallback 1', [[2027, 12, 31], 'MF', [[2027, 12, 31]]], [2027, 12, 30]], ['regression modified following fallback 2', [[2025, 8, 30], 'MF', [[2025, 9, 2], [2025, 8, 31]]], [2025, 8, 29]], ['partial repair probe 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2024, 1, 4], [2023, 12, 29]]], [2023, 12, 28]], ['boundary control 1', [[2024, 5, 15], 'X', []], 'unknown convention'], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2030, 12, 21], 'F', [[2030, 12, 18], [2030, 12, 20], [2030, 12, 18]]], [2030, 12, 23]], ['normal control 2', [[2024, 7, 31], 'MP', [[2024, 8, 2], [2024, 7, 29]]], [2024, 7, 31]]], [['regression modified following fallback 1', [[2023, 12, 31], 'MF', []], [2023, 12, 29]], ['regression modified following fallback 2', [[2026, 2, 28], 'MF', []], [2026, 2, 27]], ['partial repair probe 1', [[2023, 4, 30], 'MF', [[2023, 4, 29], [2023, 5, 1]]], [2023, 4, 28]], ['partial repair probe 2', [[2023, 12, 31], 'MF', [[2023, 12, 31]]], [2023, 12, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['normal control 1', [[2023, 11, 4], 'F', []], [2023, 11, 6]], ['normal control 2', [[2025, 9, 1], 'X', [[2025, 9, 4]]], 'unknown convention']], [['regression modified following fallback 1', [[2030, 3, 31], 'MF', [[2030, 3, 28], [2030, 4, 4]]], [2030, 3, 29]], ['regression modified following fallback 2', [[2024, 8, 29], 'MF', [[2024, 8, 30], [2024, 8, 29]]], [2024, 8, 28]], ['partial repair probe 1', [[2024, 6, 29], 'MF', [[2024, 7, 2], [2024, 6, 28]]], [2024, 6, 27]], ['partial repair probe 2', [[2028, 12, 31], 'MF', [[2028, 12, 29], [2029, 1, 1]]], [2028, 12, 28]], ['boundary control 1', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2026, 1, 18], 'MP', [[2026, 1, 21]]], [2026, 1, 16]], ['normal control 2', [[2020, 6, 1], 'MP', [[2020, 5, 30], [2020, 6, 5], [2020, 5, 30]]], [2020, 6, 1]]], [['regression modified following fallback 1', [[2020, 5, 31], 'MF', []], [2020, 5, 29]], ['regression modified following fallback 2', [[2022, 12, 31], 'MF', []], [2022, 12, 30]], ['partial repair probe 1', [[2021, 10, 31], 'MF', []], [2021, 10, 29]], ['partial repair probe 2', [[2019, 3, 31], 'MF', [[2019, 3, 30]]], [2019, 3, 29]], ['boundary control 1', [[2024, 5, 15], 'F', [[2024, 5, 15]]], [2024, 5, 16]], ['boundary control 2', [[2024, 5, 15], 'X', []], 'unknown convention'], ['normal control 1', [[2028, 4, 30], 'P', []], [2028, 4, 28]], ['normal control 2', [[2028, 11, 30], 'X', []], 'unknown convention']], [['regression modified following fallback 1', [[2025, 12, 31], 'MF', [[2025, 12, 31]]], [2025, 12, 30]], ['regression modified following fallback 2', [[2027, 1, 31], 'MF', []], [2027, 1, 29]], ['partial repair probe 1', [[2024, 3, 31], 'MF', [[2024, 3, 30]]], [2024, 3, 29]], ['partial repair probe 2', [[2028, 12, 31], 'MF', []], [2028, 12, 29]], ['boundary control 1', [[2024, 6, 1], 'MP', []], [2024, 6, 3]], ['boundary control 2', [[2024, 12, 28], 'F', []], [2024, 12, 30]], ['normal control 1', [[2023, 3, 29], 'MP', [[2023, 3, 28], [2023, 3, 31]]], [2023, 3, 29]], ['normal control 2', [[2026, 10, 1], 'MP', []], [2026, 10, 1]]]]\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 contract stated explicitly in the contract field; no claim of conformance to any published convention text. 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-bond_day_count_conventions-business-day-adjustment-modified-following-fallback","generated_at":"2026-09-29T14:46:50.722542+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Bond accrual and pricing systems depend on exact day-count arithmetic; a single-day error changes settlement cash.","repair":"Roll back from the original date when the forward roll leaves the month.","root_cause":"After detecting a month change the fallback rolls back from the already-rolled business date, which does not move.","sha256":"5ee0fe7e3a771bf6b5b8a51f35b083fc5471d1185c8b5b83e9f89c2c57830bcd","title":"Business day adjustment conventions: the month-crossing fallback steps back from the rolled date · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":42.641,"exit_code":1,"observations":[{"actual":[2027,12,30],"check":"regression modified following fallback 1","expected":[2027,12,30],"passed":true},{"actual":[2025,8,29],"check":"regression modified following fallback 2","expected":[2025,8,29],"passed":true},{"actual":[2023,12,30],"check":"partial repair probe 1","expected":[2023,12,29],"passed":false},{"actual":[2023,12,30],"check":"partial repair probe 2","expected":[2023,12,28],"passed":false},{"actual":"unknown convention","check":"boundary control 1","expected":"unknown convention","passed":true},{"actual":[2024,12,30],"check":"boundary control 2","expected":[2024,12,30],"passed":true},{"actual":[2030,12,23],"check":"normal control 1","expected":[2030,12,23],"passed":true},{"actual":[2024,7,31],"check":"normal control 2","expected":[2024,7,31],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression modified following fallback 1\", \"actual\": [2027, 12, 30], \"expected\": [2027, 12, 30], \"passed\": true}, {\"check\": \"regression modified following fallback 2\", \"actual\": [2025, 8, 29], \"expected\": [2025, 8, 29], \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": [2023, 12, 30], \"expected\": [2023, 12, 29], \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": [2023, 12, 30], \"expected\": [2023, 12, 28], \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": \"unknown convention\", \"expected\": \"unknown convention\", \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": [2024, 12, 30], \"expected\": [2024, 12, 30], \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": [2030, 12, 23], \"expected\": [2030, 12, 23], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [2024, 7, 31], \"expected\": [2024, 7, 31], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":49.57,"exit_code":1,"observations":[{"actual":[2028,1,3],"check":"regression modified following fallback 1","expected":[2027,12,30],"passed":false},{"actual":[2025,9,1],"check":"regression modified following fallback 2","expected":[2025,8,29],"passed":false},{"actual":[2024,1,1],"check":"partial repair probe 1","expected":[2023,12,29],"passed":false},{"actual":[2024,1,1],"check":"partial repair probe 2","expected":[2023,12,28],"passed":false},{"actual":"unknown convention","check":"boundary control 1","expected":"unknown convention","passed":true},{"actual":[2024,12,30],"check":"boundary control 2","expected":[2024,12,30],"passed":true},{"actual":[2030,12,23],"check":"normal control 1","expected":[2030,12,23],"passed":true},{"actual":[2024,7,31],"check":"normal control 2","expected":[2024,7,31],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression modified following fallback 1\", \"actual\": [2028, 1, 3], \"expected\": [2027, 12, 30], \"passed\": false}, {\"check\": \"regression modified following fallback 2\", \"actual\": [2025, 9, 1], \"expected\": [2025, 8, 29], \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": [2024, 1, 1], \"expected\": [2023, 12, 29], \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": [2024, 1, 1], \"expected\": [2023, 12, 28], \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": \"unknown convention\", \"expected\": \"unknown convention\", \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": [2024, 12, 30], \"expected\": [2024, 12, 30], \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": [2030, 12, 23], \"expected\": [2030, 12, 23], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [2024, 7, 31], \"expected\": [2024, 7, 31], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":44.656,"exit_code":0,"observations":[{"actual":[2027,12,30],"check":"regression modified following fallback 1","expected":[2027,12,30],"passed":true},{"actual":[2025,8,29],"check":"regression modified following fallback 2","expected":[2025,8,29],"passed":true},{"actual":[2023,12,29],"check":"partial repair probe 1","expected":[2023,12,29],"passed":true},{"actual":[2023,12,28],"check":"partial repair probe 2","expected":[2023,12,28],"passed":true},{"actual":"unknown convention","check":"boundary control 1","expected":"unknown convention","passed":true},{"actual":[2024,12,30],"check":"boundary control 2","expected":[2024,12,30],"passed":true},{"actual":[2030,12,23],"check":"normal control 1","expected":[2030,12,23],"passed":true},{"actual":[2024,7,31],"check":"normal control 2","expected":[2024,7,31],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression modified following fallback 1\", \"actual\": [2027, 12, 30], \"expected\": [2027, 12, 30], \"passed\": true}, {\"check\": \"regression modified following fallback 2\", \"actual\": [2025, 8, 29], \"expected\": [2025, 8, 29], \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": [2023, 12, 29], \"expected\": [2023, 12, 29], \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": [2023, 12, 28], \"expected\": [2023, 12, 28], \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": \"unknown convention\", \"expected\": \"unknown convention\", \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": [2024, 12, 30], \"expected\": [2024, 12, 30], \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": [2030, 12, 23], \"expected\": [2030, 12, 23], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [2024, 7, 31], \"expected\": [2024, 7, 31], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}