{"abstract":"Phases that started before the period charge for days in the previous period.","category":"Subscription proration billing","checks":8,"contract":"Input {ps, pe (exclusive), phases: [[start_day, price per full period]]}. Phases are ordered by start; each lasts until the next phase starts (the last until pe). The period charge is sum(price * overlap days with [ps, pe)) / (pe - ps), rounded half-up once. Return cents.","evaluation_group":"w2-subscription-proration-schedule-phase-invoice","failed_approach":"The attempt takes the earlier of the two starts, still reaching back into the previous period.","family":"w2-subscription-proration-schedule-phase-invoice-overlap-start-clip","id":"FA-59706","implementations":{"attempt":{"sha256":"82334d4c30df7b0daa4a3fc16ef536552682c0fcf4df86f27b2d9b40e6bff138","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    ph = sorted(x['phases'], key=lambda p: p[0])\n    L = x['pe'] - x['ps']\n    total = 0\n    for i, (st, price) in enumerate(ph):\n        en = ph[i + 1][0] if i + 1 < len(ph) else x['pe']\n        a, b = min(st, x['ps']), min(en, x['pe'])\n        if b > a:\n            total += price * (b - a)\n    return (total * 2 + L) // (2 * L)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'ps': 30, 'pe': 60, 'phases': [[53, 0], [60, 2000], [12, 3500], [36, 2000]]}, 1833), ('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('partial-repair probe', {'ps': 15, 'pe': 45, 'phases': [[45, 3500], [27, 1000], [39, 1957]]}, 791), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[73, 0]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[23, 0], [58, 0]]}, 0), ('normal control', {'ps': 56, 'pe': 86, 'phases': [[60, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[101, 0], [118, 0], [118, 0]]}, 0)], [('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('normal control', {'ps': 95, 'pe': 125, 'phases': [[105, 0]]}, 0), ('normal control', {'ps': 62, 'pe': 92, 'phases': [[62, 1000]]}, 1000), ('normal control', {'ps': 74, 'pe': 104, 'phases': [[58, 0], [77, 0]]}, 0), ('normal control', {'ps': 53, 'pe': 84, 'phases': [[77, 0]]}, 0)], [('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('partial-repair probe', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('normal control', {'ps': 2, 'pe': 32, 'phases': [[-18, 0]]}, 0), ('normal control', {'ps': 84, 'pe': 115, 'phases': [[84, 996], [96, 0]]}, 386), ('normal control', {'ps': 9, 'pe': 39, 'phases': [[17, 0]]}, 0), ('normal control', {'ps': 0, 'pe': 30, 'phases': [[-20, 0]]}, 0)], [('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('normal control', {'ps': 78, 'pe': 109, 'phases': [[104, 0], [114, 0], [68, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[94, 0]]}, 0), ('normal control', {'ps': 91, 'pe': 122, 'phases': [[117, 0]]}, 0), ('normal control', {'ps': 44, 'pe': 74, 'phases': [[68, 0], [54, 0], [31, 0]]}, 0)], [('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('regression', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 74, 'pe': 104, 'phases': [[63, 2000], [89, 1000]]}, 1500), ('normal control', {'ps': 42, 'pe': 73, 'phases': [[75, 0]]}, 0), ('normal control', {'ps': 82, 'pe': 113, 'phases': [[82, 0]]}, 0), ('normal control', {'ps': 5, 'pe': 36, 'phases': [[22, 0]]}, 0), ('normal control', {'ps': 2, 'pe': 33, 'phases': [[-16, 0]]}, 0)]]\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":"97747738d0734af75da6b53e75aa355309799a23607bcd1a4bb641d165cf136c","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    ph = sorted(x['phases'], key=lambda p: p[0])\n    L = x['pe'] - x['ps']\n    total = 0\n    for i, (st, price) in enumerate(ph):\n        en = ph[i + 1][0] if i + 1 < len(ph) else x['pe']\n        a, b = st, min(en, x['pe'])\n        if b > a:\n            total += price * (b - a)\n    return (total * 2 + L) // (2 * L)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'ps': 30, 'pe': 60, 'phases': [[53, 0], [60, 2000], [12, 3500], [36, 2000]]}, 1833), ('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('partial-repair probe', {'ps': 15, 'pe': 45, 'phases': [[45, 3500], [27, 1000], [39, 1957]]}, 791), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[73, 0]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[23, 0], [58, 0]]}, 0), ('normal control', {'ps': 56, 'pe': 86, 'phases': [[60, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[101, 0], [118, 0], [118, 0]]}, 0)], [('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('normal control', {'ps': 95, 'pe': 125, 'phases': [[105, 0]]}, 0), ('normal control', {'ps': 62, 'pe': 92, 'phases': [[62, 1000]]}, 1000), ('normal control', {'ps': 74, 'pe': 104, 'phases': [[58, 0], [77, 0]]}, 0), ('normal control', {'ps': 53, 'pe': 84, 'phases': [[77, 0]]}, 0)], [('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('partial-repair probe', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('normal control', {'ps': 2, 'pe': 32, 'phases': [[-18, 0]]}, 0), ('normal control', {'ps': 84, 'pe': 115, 'phases': [[84, 996], [96, 0]]}, 386), ('normal control', {'ps': 9, 'pe': 39, 'phases': [[17, 0]]}, 0), ('normal control', {'ps': 0, 'pe': 30, 'phases': [[-20, 0]]}, 0)], [('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('normal control', {'ps': 78, 'pe': 109, 'phases': [[104, 0], [114, 0], [68, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[94, 0]]}, 0), ('normal control', {'ps': 91, 'pe': 122, 'phases': [[117, 0]]}, 0), ('normal control', {'ps': 44, 'pe': 74, 'phases': [[68, 0], [54, 0], [31, 0]]}, 0)], [('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('regression', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 74, 'pe': 104, 'phases': [[63, 2000], [89, 1000]]}, 1500), ('normal control', {'ps': 42, 'pe': 73, 'phases': [[75, 0]]}, 0), ('normal control', {'ps': 82, 'pe': 113, 'phases': [[82, 0]]}, 0), ('normal control', {'ps': 5, 'pe': 36, 'phases': [[22, 0]]}, 0), ('normal control', {'ps': 2, 'pe': 33, 'phases': [[-16, 0]]}, 0)]]\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":"412dd44297292364d9632bcde2555986ad7db81a7a1c7f149f11d408801641f6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    ph = sorted(x['phases'], key=lambda p: p[0])\n    L = x['pe'] - x['ps']\n    total = 0\n    for i, (st, price) in enumerate(ph):\n        en = ph[i + 1][0] if i + 1 < len(ph) else x['pe']\n        a, b = max(st, x['ps']), min(en, x['pe'])\n        if b > a:\n            total += price * (b - a)\n    return (total * 2 + L) // (2 * L)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'ps': 30, 'pe': 60, 'phases': [[53, 0], [60, 2000], [12, 3500], [36, 2000]]}, 1833), ('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('partial-repair probe', {'ps': 15, 'pe': 45, 'phases': [[45, 3500], [27, 1000], [39, 1957]]}, 791), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[73, 0]]}, 0), ('normal control', {'ps': 42, 'pe': 72, 'phases': [[23, 0], [58, 0]]}, 0), ('normal control', {'ps': 56, 'pe': 86, 'phases': [[60, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[101, 0], [118, 0], [118, 0]]}, 0)], [('regression', {'ps': 54, 'pe': 84, 'phases': [[70, 3500], [48, 3500], [40, 5707], [49, 0]]}, 1633), ('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('partial-repair probe', {'ps': 95, 'pe': 125, 'phases': [[126, 434]]}, 0), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('normal control', {'ps': 95, 'pe': 125, 'phases': [[105, 0]]}, 0), ('normal control', {'ps': 62, 'pe': 92, 'phases': [[62, 1000]]}, 1000), ('normal control', {'ps': 74, 'pe': 104, 'phases': [[58, 0], [77, 0]]}, 0), ('normal control', {'ps': 53, 'pe': 84, 'phases': [[77, 0]]}, 0)], [('regression', {'ps': 52, 'pe': 82, 'phases': [[60, 0], [44, 1000], [60, 1000], [32, 1000]]}, 1000), ('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('partial-repair probe', {'ps': 25, 'pe': 55, 'phases': [[40, 6111], [52, 7893], [43, 3500]]}, 2450), ('partial-repair probe', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('normal control', {'ps': 2, 'pe': 32, 'phases': [[-18, 0]]}, 0), ('normal control', {'ps': 84, 'pe': 115, 'phases': [[84, 996], [96, 0]]}, 386), ('normal control', {'ps': 9, 'pe': 39, 'phases': [[17, 0]]}, 0), ('normal control', {'ps': 0, 'pe': 30, 'phases': [[-20, 0]]}, 0)], [('regression', {'ps': 21, 'pe': 52, 'phases': [[29, 6784], [10, 1000], [29, 5303], [34, 1000]]}, 1694), ('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('normal control', {'ps': 78, 'pe': 109, 'phases': [[104, 0], [114, 0], [68, 0]]}, 0), ('normal control', {'ps': 90, 'pe': 121, 'phases': [[94, 0]]}, 0), ('normal control', {'ps': 91, 'pe': 122, 'phases': [[117, 0]]}, 0), ('normal control', {'ps': 44, 'pe': 74, 'phases': [[68, 0], [54, 0], [31, 0]]}, 0)], [('regression', {'ps': 47, 'pe': 77, 'phases': [[42, 1000], [68, 2000]]}, 1300), ('regression', {'ps': 9, 'pe': 40, 'phases': [[-1, 2000], [3, 3500]]}, 3500), ('partial-repair probe', {'ps': 87, 'pe': 117, 'phases': [[84, 0], [119, 2000]]}, 0), ('partial-repair probe', {'ps': 74, 'pe': 104, 'phases': [[63, 2000], [89, 1000]]}, 1500), ('normal control', {'ps': 42, 'pe': 73, 'phases': [[75, 0]]}, 0), ('normal control', {'ps': 82, 'pe': 113, 'phases': [[82, 0]]}, 0), ('normal control', {'ps': 5, 'pe': 36, 'phases': [[22, 0]]}, 0), ('normal control', {'ps': 2, 'pe': 33, 'phases': [[-16, 0]]}, 0)]]\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-schedule-phase-invoice-overlap-start-clip","generated_at":"2026-09-29T14:46:38.828198+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Phase transitions inside a billing period must be charged exactly for their overlapping days.","repair":"Restore the contract rule at the overlap start clip step: use `a, b = max(st, x['ps']), min(en, x['pe'])`.","root_cause":"The overlap start is not clipped to the period start.","sha256":"097f5eb4a9144de03222f536ab757cd1f912ad914405321e03c2667a78b4448b","title":"Subscription schedule phases within a period: overlap start clip · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.437,"exit_code":1,"observations":[{"actual":6333,"check":"regression 0","expected":1833,"passed":false},{"actual":5139,"check":"regression 1","expected":1633,"passed":false},{"actual":6257,"check":"partial-repair probe 2","expected":791,"passed":false},{"actual":434,"check":"partial-repair probe 3","expected":0,"passed":false},{"actual":0,"check":"normal control 4","expected":0,"passed":true},{"actual":0,"check":"normal control 5","expected":0,"passed":true},{"actual":0,"check":"normal control 6","expected":0,"passed":true},{"actual":0,"check":"normal control 7","expected":0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": 6333, \"expected\": 1833, \"passed\": false}, {\"check\": \"regression 1\", \"actual\": 5139, \"expected\": 1633, \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": 6257, \"expected\": 791, \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": 434, \"expected\": 0, \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": 0, \"expected\": 0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":37.985,"exit_code":1,"observations":[{"actual":3933,"check":"regression 0","expected":1833,"passed":false},{"actual":3272,"check":"regression 1","expected":1633,"passed":false},{"actual":791,"check":"partial-repair probe 2","expected":791,"passed":true},{"actual":0,"check":"partial-repair probe 3","expected":0,"passed":true},{"actual":0,"check":"normal control 4","expected":0,"passed":true},{"actual":0,"check":"normal control 5","expected":0,"passed":true},{"actual":0,"check":"normal control 6","expected":0,"passed":true},{"actual":0,"check":"normal control 7","expected":0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": 3933, \"expected\": 1833, \"passed\": false}, {\"check\": \"regression 1\", \"actual\": 3272, \"expected\": 1633, \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": 791, \"expected\": 791, \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": 0, \"expected\": 0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":38.002,"exit_code":0,"observations":[{"actual":1833,"check":"regression 0","expected":1833,"passed":true},{"actual":1633,"check":"regression 1","expected":1633,"passed":true},{"actual":791,"check":"partial-repair probe 2","expected":791,"passed":true},{"actual":0,"check":"partial-repair probe 3","expected":0,"passed":true},{"actual":0,"check":"normal control 4","expected":0,"passed":true},{"actual":0,"check":"normal control 5","expected":0,"passed":true},{"actual":0,"check":"normal control 6","expected":0,"passed":true},{"actual":0,"check":"normal control 7","expected":0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": 1833, \"expected\": 1833, \"passed\": true}, {\"check\": \"regression 1\", \"actual\": 1633, \"expected\": 1633, \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": 791, \"expected\": 791, \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": 0, \"expected\": 0, \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": 0, \"expected\": 0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}