{"abstract":"A change on a renewal date is prorated against the period that just ended.","category":"Subscription proration billing","checks":7,"contract":"Input {anchor, interval week|month|year, count, at >= anchor}. Period k starts at anchor + k*count intervals (weeks as 7 days; months/years by calendar month with the anchor day clamped to month length). Return [start ISO, end ISO] of the period with start <= at < end.","evaluation_group":"w2-subscription-proration-current-period-lookup","failed_approach":"The attempt advances while the current start is before the date, overshooting by one period.","family":"w2-subscription-proration-current-period-lookup-boundary-date-ownership","id":"FA-59721","implementations":{"attempt":{"sha256":"972331d3ea0763b7f21605f9def1368904203e20532ee8ff6bfbbe04c53e1adc","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nimport calendar\nN = 1\nobservations = []\ndef solve(x):\n    a = datetime.date(*x['anchor'])\n    t = datetime.date(*x['at'])\n    def shift(k):\n        if x['interval'] == 'week':\n            return a + datetime.timedelta(days=7 * x['count'] * k)\n        months = k * x['count'] * (12 if x['interval'] == 'year' else 1)\n        tot = a.month - 1 + months\n        y, m = a.year + tot // 12, tot % 12 + 1\n        return datetime.date(y, m, min(a.day, calendar.monthrange(y, m)[1]))\n    k = 0\n    while shift(k) < t:\n        k += 1\n    return [shift(k).isoformat(), shift(k + 1).isoformat()]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2024, 1, 31], 'interval': 'month', 'count': 1, 'at': [2024, 2, 29]}, ['2024-02-29', '2024-03-31']), ('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('partial-repair probe', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('partial-repair probe', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])], [('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('partial-repair probe', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19']), ('partial-repair probe', {'anchor': [2020, 8, 2], 'interval': 'week', 'count': 3, 'at': [2020, 9, 4]}, ['2020-08-23', '2020-09-13']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('partial-repair probe', {'anchor': [2021, 11, 24], 'interval': 'year', 'count': 3, 'at': [2022, 4, 18]}, ['2021-11-24', '2024-11-24']), ('partial-repair probe', {'anchor': [2020, 8, 7], 'interval': 'week', 'count': 2, 'at': [2023, 10, 30]}, ['2023-10-27', '2023-11-10']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('partial-repair probe', {'anchor': [2021, 2, 28], 'interval': 'year', 'count': 2, 'at': [2021, 8, 29]}, ['2021-02-28', '2023-02-28']), ('partial-repair probe', {'anchor': [2020, 11, 28], 'interval': 'year', 'count': 2, 'at': [2023, 9, 6]}, ['2022-11-28', '2024-11-28']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31'])], [('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('regression', {'anchor': [2020, 7, 31], 'interval': 'month', 'count': 1, 'at': [2023, 5, 31]}, ['2023-05-31', '2023-06-30']), ('partial-repair probe', {'anchor': [2023, 12, 31], 'interval': 'month', 'count': 1, 'at': [2024, 7, 11]}, ['2024-06-30', '2024-07-31']), ('partial-repair probe', {'anchor': [2020, 2, 20], 'interval': 'month', 'count': 1, 'at': [2022, 12, 10]}, ['2022-11-20', '2022-12-20']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])]]\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":"d41b23141488d8634e1f0cfe4342897dbeb87c260fa55f44e97bfde715d37d53","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nimport calendar\nN = 1\nobservations = []\ndef solve(x):\n    a = datetime.date(*x['anchor'])\n    t = datetime.date(*x['at'])\n    def shift(k):\n        if x['interval'] == 'week':\n            return a + datetime.timedelta(days=7 * x['count'] * k)\n        months = k * x['count'] * (12 if x['interval'] == 'year' else 1)\n        tot = a.month - 1 + months\n        y, m = a.year + tot // 12, tot % 12 + 1\n        return datetime.date(y, m, min(a.day, calendar.monthrange(y, m)[1]))\n    k = 0\n    while shift(k + 1) < t:\n        k += 1\n    return [shift(k).isoformat(), shift(k + 1).isoformat()]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2024, 1, 31], 'interval': 'month', 'count': 1, 'at': [2024, 2, 29]}, ['2024-02-29', '2024-03-31']), ('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('partial-repair probe', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('partial-repair probe', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])], [('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('partial-repair probe', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19']), ('partial-repair probe', {'anchor': [2020, 8, 2], 'interval': 'week', 'count': 3, 'at': [2020, 9, 4]}, ['2020-08-23', '2020-09-13']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('partial-repair probe', {'anchor': [2021, 11, 24], 'interval': 'year', 'count': 3, 'at': [2022, 4, 18]}, ['2021-11-24', '2024-11-24']), ('partial-repair probe', {'anchor': [2020, 8, 7], 'interval': 'week', 'count': 2, 'at': [2023, 10, 30]}, ['2023-10-27', '2023-11-10']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('partial-repair probe', {'anchor': [2021, 2, 28], 'interval': 'year', 'count': 2, 'at': [2021, 8, 29]}, ['2021-02-28', '2023-02-28']), ('partial-repair probe', {'anchor': [2020, 11, 28], 'interval': 'year', 'count': 2, 'at': [2023, 9, 6]}, ['2022-11-28', '2024-11-28']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31'])], [('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('regression', {'anchor': [2020, 7, 31], 'interval': 'month', 'count': 1, 'at': [2023, 5, 31]}, ['2023-05-31', '2023-06-30']), ('partial-repair probe', {'anchor': [2023, 12, 31], 'interval': 'month', 'count': 1, 'at': [2024, 7, 11]}, ['2024-06-30', '2024-07-31']), ('partial-repair probe', {'anchor': [2020, 2, 20], 'interval': 'month', 'count': 1, 'at': [2022, 12, 10]}, ['2022-11-20', '2022-12-20']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])]]\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":"9f4fc47716d9b58fd0eac9503bd482053c4034be156da8b5af1783f486e466f6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport datetime\nimport calendar\nN = 1\nobservations = []\ndef solve(x):\n    a = datetime.date(*x['anchor'])\n    t = datetime.date(*x['at'])\n    def shift(k):\n        if x['interval'] == 'week':\n            return a + datetime.timedelta(days=7 * x['count'] * k)\n        months = k * x['count'] * (12 if x['interval'] == 'year' else 1)\n        tot = a.month - 1 + months\n        y, m = a.year + tot // 12, tot % 12 + 1\n        return datetime.date(y, m, min(a.day, calendar.monthrange(y, m)[1]))\n    k = 0\n    while shift(k + 1) <= t:\n        k += 1\n    return [shift(k).isoformat(), shift(k + 1).isoformat()]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression (boundary)', {'anchor': [2024, 1, 31], 'interval': 'month', 'count': 1, 'at': [2024, 2, 29]}, ['2024-02-29', '2024-03-31']), ('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('partial-repair probe', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('partial-repair probe', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])], [('regression (boundary)', {'anchor': [2024, 1, 10], 'interval': 'week', 'count': 2, 'at': [2024, 1, 24]}, ['2024-01-24', '2024-02-07']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('partial-repair probe', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19']), ('partial-repair probe', {'anchor': [2020, 8, 2], 'interval': 'week', 'count': 3, 'at': [2020, 9, 4]}, ['2020-08-23', '2020-09-13']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('partial-repair probe', {'anchor': [2021, 11, 24], 'interval': 'year', 'count': 3, 'at': [2022, 4, 18]}, ['2021-11-24', '2024-11-24']), ('partial-repair probe', {'anchor': [2020, 8, 7], 'interval': 'week', 'count': 2, 'at': [2023, 10, 30]}, ['2023-10-27', '2023-11-10']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2020, 10, 31], 'interval': 'year', 'count': 1, 'at': [2022, 2, 15]}, ['2021-10-31', '2022-10-31']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29'])], [('regression', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 1, 'at': [2023, 11, 30]}, ['2023-11-30', '2023-12-31']), ('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('partial-repair probe', {'anchor': [2021, 2, 28], 'interval': 'year', 'count': 2, 'at': [2021, 8, 29]}, ['2021-02-28', '2023-02-28']), ('partial-repair probe', {'anchor': [2020, 11, 28], 'interval': 'year', 'count': 2, 'at': [2023, 9, 6]}, ['2022-11-28', '2024-11-28']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2023, 10, 31], 'interval': 'month', 'count': 2, 'at': [2024, 2, 3]}, ['2023-12-31', '2024-02-29']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31'])], [('regression', {'anchor': [2022, 8, 21], 'interval': 'week', 'count': 1, 'at': [2025, 1, 26]}, ['2025-01-26', '2025-02-02']), ('regression', {'anchor': [2020, 7, 31], 'interval': 'month', 'count': 1, 'at': [2023, 5, 31]}, ['2023-05-31', '2023-06-30']), ('partial-repair probe', {'anchor': [2023, 12, 31], 'interval': 'month', 'count': 1, 'at': [2024, 7, 11]}, ['2024-06-30', '2024-07-31']), ('partial-repair probe', {'anchor': [2020, 2, 20], 'interval': 'month', 'count': 1, 'at': [2022, 12, 10]}, ['2022-11-20', '2022-12-20']), ('normal control', {'anchor': [2020, 1, 1], 'interval': 'week', 'count': 2, 'at': [2020, 1, 1]}, ['2020-01-01', '2020-01-15']), ('additional oracle', {'anchor': [2022, 10, 31], 'interval': 'month', 'count': 2, 'at': [2023, 6, 30]}, ['2023-06-30', '2023-08-31']), ('additional oracle', {'anchor': [2023, 5, 19], 'interval': 'year', 'count': 1, 'at': [2025, 8, 18]}, ['2025-05-19', '2026-05-19'])]]\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 billing rule. It makes no claim to reproduce any billing provider's exact behaviour and is not billing 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-subscription-proration-current-period-lookup-boundary-date-ownership","generated_at":"2026-09-29T14:46:38.871657+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Proration needs the exact period containing a change date; boundary dates belong to the new period.","repair":"Restore the contract rule at the boundary date ownership step: use `while shift(k + 1) <= t:`.","root_cause":"A date equal to the next period start is kept in the previous period.","sha256":"697a451b8f05ea9c63b05bb7ff806fec68070dbd5b2e6515909dd432c526fd8c","title":"Current billing period containing a date: boundary date ownership · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":43.227,"exit_code":1,"observations":[{"actual":["2024-02-29","2024-03-31"],"check":"regression (boundary) 0","expected":["2024-02-29","2024-03-31"],"passed":true},{"actual":["2024-01-24","2024-02-07"],"check":"regression (boundary) 1","expected":["2024-01-24","2024-02-07"],"passed":true},{"actual":["2022-10-31","2023-10-31"],"check":"partial-repair probe 2","expected":["2021-10-31","2022-10-31"],"passed":false},{"actual":["2024-02-29","2024-04-30"],"check":"partial-repair probe 3","expected":["2023-12-31","2024-02-29"],"passed":false},{"actual":["2020-01-01","2020-01-15"],"check":"normal control 4","expected":["2020-01-01","2020-01-15"],"passed":true},{"actual":["2023-06-30","2023-08-31"],"check":"additional oracle 5","expected":["2023-06-30","2023-08-31"],"passed":true},{"actual":["2026-05-19","2027-05-19"],"check":"additional oracle 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4\", \"actual\": [\"2020-01-01\", \"2020-01-15\"], \"expected\": [\"2020-01-01\", \"2020-01-15\"], \"passed\": true}, {\"check\": \"additional oracle 5\", \"actual\": [\"2023-06-30\", \"2023-08-31\"], \"expected\": [\"2023-06-30\", \"2023-08-31\"], \"passed\": true}, {\"check\": \"additional oracle 6\", \"actual\": [\"2025-05-19\", \"2026-05-19\"], \"expected\": [\"2025-05-19\", \"2026-05-19\"], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}