{"abstract":"The first pay date reported for a year falls in December of the prior year.","category":"Payroll withholding rules","checks":7,"contract":"Input {anchor [y,m,d] (any pay date), step 7|14 days, year}. Pay dates are anchor + k*step for all integers k. Return [count of pay dates within Jan 1..Dec 31 of year inclusive, ISO date of the first one, whether the count exceeds the nominal periods (26 biweekly, 52 weekly)].","evaluation_group":"w2-payroll-withholding-pay-date-count","failed_approach":"The attempt adds one step, skipping a pay date that falls exactly on January 1.","family":"w2-payroll-withholding-pay-date-count-first-pay-date-ceiling","id":"FA-59221","implementations":{"attempt":{"sha256":"74c330b7196df0c9c2fb809957559beca28fbaa7e3c7ba4e70992020450af3d9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nN = 1\nobservations = []\ndef solve(x):\n    anchor = datetime.date(*x['anchor'])\n    lo = datetime.date(x['year'], 1, 1)\n    hi = datetime.date(x['year'], 12, 31)\n    off = (lo - anchor).days\n    k = off // x['step'] + 1\n    first = anchor + datetime.timedelta(days=k * x['step'])\n    count = (hi - first).days // x['step'] + 1\n    periods = 26 if x['step'] == 14 else 52\n    return [count, first.isoformat(), count > periods]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('partial-repair probe (boundary)', {'anchor': [2026, 1, 1], 'step': 14, 'year': 2026}, [27, '2026-01-01', True]), ('partial-repair probe', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('partial-repair probe', {'anchor': [2024, 10, 14], 'step': 7, 'year': 2024}, [53, '2024-01-01', True]), ('partial-repair probe', {'anchor': [2021, 1, 17], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('partial-repair probe', {'anchor': [2019, 8, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('partial-repair probe', {'anchor': [2025, 3, 13], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False])], [('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('partial-repair probe', {'anchor': [2024, 10, 27], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2018, 3, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False])], [('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('regression', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('partial-repair probe', {'anchor': [2021, 5, 2], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2025, 9, 4], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False]), ('additional oracle', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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":"72c737cc95120db401c2770d6ae9b311bfada8fc2906eb0637040cf3bad6543e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nN = 1\nobservations = []\ndef solve(x):\n    anchor = datetime.date(*x['anchor'])\n    lo = datetime.date(x['year'], 1, 1)\n    hi = datetime.date(x['year'], 12, 31)\n    off = (lo - anchor).days\n    k = off // x['step']\n    first = anchor + datetime.timedelta(days=k * x['step'])\n    count = (hi - first).days // x['step'] + 1\n    periods = 26 if x['step'] == 14 else 52\n    return [count, first.isoformat(), count > periods]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('partial-repair probe (boundary)', {'anchor': [2026, 1, 1], 'step': 14, 'year': 2026}, [27, '2026-01-01', True]), ('partial-repair probe', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('partial-repair probe', {'anchor': [2024, 10, 14], 'step': 7, 'year': 2024}, [53, '2024-01-01', True]), ('partial-repair probe', {'anchor': [2021, 1, 17], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('partial-repair probe', {'anchor': [2019, 8, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('partial-repair probe', {'anchor': [2025, 3, 13], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False])], [('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('partial-repair probe', {'anchor': [2024, 10, 27], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2018, 3, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False])], [('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('regression', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('partial-repair probe', {'anchor': [2021, 5, 2], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2025, 9, 4], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False]), ('additional oracle', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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":"75890b16fa91057aa29f651cc6a7dcfb1d2f735346e9bc8d0a0b2ee474ecd7b6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nN = 1\nobservations = []\ndef solve(x):\n    anchor = datetime.date(*x['anchor'])\n    lo = datetime.date(x['year'], 1, 1)\n    hi = datetime.date(x['year'], 12, 31)\n    off = (lo - anchor).days\n    k = -(-off // x['step'])\n    first = anchor + datetime.timedelta(days=k * x['step'])\n    count = (hi - first).days // x['step'] + 1\n    periods = 26 if x['step'] == 14 else 52\n    return [count, first.isoformat(), count > periods]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('partial-repair probe (boundary)', {'anchor': [2026, 1, 1], 'step': 14, 'year': 2026}, [27, '2026-01-01', True]), ('partial-repair probe', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('partial-repair probe', {'anchor': [2024, 10, 14], 'step': 7, 'year': 2024}, [53, '2024-01-01', True]), ('partial-repair probe', {'anchor': [2021, 1, 17], 'step': 14, 'year': 2023}, [27, '2023-01-01', True]), ('additional oracle (boundary)', {'anchor': [2020, 12, 31], 'step': 14, 'year': 2020}, [27, '2020-01-02', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False])], [('regression', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('partial-repair probe', {'anchor': [2019, 8, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('partial-repair probe', {'anchor': [2025, 3, 13], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle (boundary)', {'anchor': [2024, 1, 5], 'step': 14, 'year': 2024}, [26, '2024-01-05', False]), ('additional oracle', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False])], [('regression', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('partial-repair probe', {'anchor': [2024, 10, 27], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2018, 3, 28], 'step': 14, 'year': 2020}, [27, '2020-01-01', True]), ('additional oracle', {'anchor': [2023, 8, 10], 'step': 14, 'year': 2024}, [26, '2024-01-11', False]), ('additional oracle', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False])], [('regression', {'anchor': [2020, 3, 23], 'step': 14, 'year': 2020}, [26, '2020-01-13', False]), ('regression', {'anchor': [2019, 7, 21], 'step': 7, 'year': 2020}, [52, '2020-01-05', False]), ('partial-repair probe', {'anchor': [2021, 5, 2], 'step': 7, 'year': 2023}, [53, '2023-01-01', True]), ('partial-repair probe', {'anchor': [2025, 9, 4], 'step': 7, 'year': 2026}, [53, '2026-01-01', True]), ('additional oracle', {'anchor': [2024, 3, 10], 'step': 14, 'year': 2024}, [26, '2024-01-14', False]), ('additional oracle', {'anchor': [2021, 6, 11], 'step': 7, 'year': 2023}, [52, '2023-01-06', False]), ('additional oracle', {'anchor': [2021, 6, 20], 'step': 14, 'year': 2023}, [27, '2023-01-01', True])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), 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 teaching model of a stipulated payroll rule with toy thresholds and rates. It makes no claim of conformance to any tax authority, statute or jurisdiction and is not payroll software. 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-payroll-withholding-pay-date-count-first-pay-date-ceiling","generated_at":"2026-09-29T14:46:34.168441+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Annualization factors change in 27-pay-period years; missing or extra pay dates distort per-period withholding.","repair":"Restore the contract rule at the first pay date ceiling step: use `k = -(-off // x['step'])`.","root_cause":"The offset to the first in-year pay date is floored instead of ceiled.","sha256":"1094cbe5f3ac9b80be901399f103c16e3e4a8ec805a5b15a8a8350273a8137af","title":"Pay dates in a calendar year: first pay date ceiling · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":46.665,"exit_code":1,"observations":[{"actual":[27,"2020-01-02",true],"check":"regression (boundary) 0","expected":[27,"2020-01-02",true],"passed":true},{"actual":[26,"2024-01-05",false],"check":"regression (boundary) 1","expected":[26,"2024-01-05",false],"passed":true},{"actual":[26,"2026-01-15",false],"check":"partial-repair probe (boundary) 2","expected":[27,"2026-01-01",true],"passed":false},{"actual":[26,"2023-01-15",false],"check":"partial-repair probe 3","expected":[27,"2023-01-01",true],"passed":false},{"actual":[26,"2024-01-11",false],"check":"additional oracle 4","expected":[26,"2024-01-11",false],"passed":true},{"actual":[26,"2024-01-14",false],"check":"additional oracle 5","expected":[26,"2024-01-14",false],"passed":true},{"actual":[26,"2020-01-13",false],"check":"additional oracle 6","expected":[26,"2020-01-13",false],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression (boundary) 0\", \"actual\": [27, \"2020-01-02\", true], \"expected\": [27, \"2020-01-02\", true], \"passed\": true}, {\"check\": \"regression (boundary) 1\", \"actual\": [26, \"2024-01-05\", false], \"expected\": [26, \"2024-01-05\", false], \"passed\": true}, {\"check\": \"partial-repair probe (boundary) 2\", \"actual\": [26, \"2026-01-15\", false], \"expected\": [27, \"2026-01-01\", true], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [26, \"2023-01-15\", false], \"expected\": [27, \"2023-01-01\", true], \"passed\": false}, {\"check\": \"additional oracle 4\", \"actual\": [26, \"2024-01-11\", false], \"expected\": [26, \"2024-01-11\", false], \"passed\": true}, {\"check\": \"additional oracle 5\", \"actual\": [26, \"2024-01-14\", false], \"expected\": [26, \"2024-01-14\", false], \"passed\": true}, {\"check\": \"additional oracle 6\", \"actual\": [26, \"2020-01-13\", false], \"expected\": [26, \"2020-01-13\", false], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.653,"exit_code":1,"observations":[{"actual":[28,"2019-12-19",true],"check":"regression (boundary) 0","expected":[27,"2020-01-02",true],"passed":false},{"actual":[27,"2023-12-22",true],"check":"regression (boundary) 1","expected":[26,"2024-01-05",false],"passed":false},{"actual":[27,"2026-01-01",true],"check":"partial-repair probe (boundary) 2","expected":[27,"2026-01-01",true],"passed":true},{"actual":[27,"2023-01-01",true],"check":"partial-repair probe 3","expected":[27,"2023-01-01",true],"passed":true},{"actual":[27,"2023-12-28",true],"check":"additional oracle 4","expected":[26,"2024-01-11",false],"passed":false},{"actual":[27,"2023-12-31",true],"check":"additional oracle 5","expected":[26,"2024-01-14",false],"passed":false},{"actual":[27,"2019-12-30",true],"check":"additional oracle 6","expected":[26,"2020-01-13",false],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression (boundary) 0\", \"actual\": [28, \"2019-12-19\", true], \"expected\": [27, \"2020-01-02\", true], \"passed\": false}, {\"check\": \"regression (boundary) 1\", \"actual\": [27, \"2023-12-22\", true], \"expected\": [26, \"2024-01-05\", false], \"passed\": false}, {\"check\": \"partial-repair probe (boundary) 2\", \"actual\": [27, \"2026-01-01\", true], \"expected\": [27, \"2026-01-01\", true], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [27, \"2023-01-01\", true], \"expected\": [27, \"2023-01-01\", true], \"passed\": true}, {\"check\": \"additional oracle 4\", \"actual\": [27, \"2023-12-28\", true], \"expected\": [26, \"2024-01-11\", false], \"passed\": false}, {\"check\": \"additional oracle 5\", \"actual\": [27, \"2023-12-31\", true], \"expected\": [26, \"2024-01-14\", false], \"passed\": false}, {\"check\": \"additional oracle 6\", \"actual\": [27, \"2019-12-30\", true], \"expected\": [26, \"2020-01-13\", false], \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":40.333,"exit_code":0,"observations":[{"actual":[27,"2020-01-02",true],"check":"regression (boundary) 0","expected":[27,"2020-01-02",true],"passed":true},{"actual":[26,"2024-01-05",false],"check":"regression (boundary) 1","expected":[26,"2024-01-05",false],"passed":true},{"actual":[27,"2026-01-01",true],"check":"partial-repair probe (boundary) 2","expected":[27,"2026-01-01",true],"passed":true},{"actual":[27,"2023-01-01",true],"check":"partial-repair probe 3","expected":[27,"2023-01-01",true],"passed":true},{"actual":[26,"2024-01-11",false],"check":"additional oracle 4","expected":[26,"2024-01-11",false],"passed":true},{"actual":[26,"2024-01-14",false],"check":"additional oracle 5","expected":[26,"2024-01-14",false],"passed":true},{"actual":[26,"2020-01-13",false],"check":"additional oracle 6","expected":[26,"2020-01-13",false],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression (boundary) 0\", \"actual\": [27, \"2020-01-02\", true], \"expected\": [27, \"2020-01-02\", true], \"passed\": true}, {\"check\": \"regression (boundary) 1\", \"actual\": [26, \"2024-01-05\", false], \"expected\": [26, \"2024-01-05\", false], \"passed\": true}, {\"check\": \"partial-repair probe (boundary) 2\", \"actual\": [27, \"2026-01-01\", true], \"expected\": [27, \"2026-01-01\", true], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [27, \"2023-01-01\", true], \"expected\": [27, \"2023-01-01\", true], \"passed\": true}, {\"check\": \"additional oracle 4\", \"actual\": [26, \"2024-01-11\", false], \"expected\": [26, \"2024-01-11\", false], \"passed\": true}, {\"check\": \"additional oracle 5\", \"actual\": [26, \"2024-01-14\", false], \"expected\": [26, \"2024-01-14\", false], \"passed\": true}, {\"check\": \"additional oracle 6\", \"actual\": [26, \"2020-01-13\", false], \"expected\": [26, \"2020-01-13\", false], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}