{"abstract":"Customers switching mid-month are credited for the month they are already using.","category":"Subscription proration billing","checks":8,"contract":"Input {annual, months_used, days_into_month, month_days, monthly}. Months started = months_used plus one if the current month has begun (days_into_month > 0), capped at 12. Credit = annual*(12 - started)//12. The credit pays whole future monthly invoices; the remainder stays as balance. Return [credit, covered_invoices, leftover].","contract_signature":"x","evaluation_group":"w2-subscription-proration-annual-to-monthly-credit","failed_approach":"The attempt counts the month as used only past its midpoint.","family":"w2-subscription-proration-annual-to-monthly-credit-partial-month-counted-as-used","id":"FA-59541","implementations":{"attempt":{"sha256":"879d17e2a885649515e8216026e22396b9ab59545fea867f7a95fcacc351961e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    started = x['months_used'] + (1 if x['days_into_month'] > x['month_days'] // 2 else 0)\n    started = min(started, 12)\n    credit = x['annual'] * (12 - started) // 12\n    covered = credit // x['monthly']\n    left = credit - covered * x['monthly']\n    return [credit, covered, left]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'annual': 119900, 'months_used': 4, 'days_into_month': 1, 'month_days': 30, 'monthly': 999}, [69941, 70, 11]), ('regression', {'annual': 12000, 'months_used': 9, 'days_into_month': 16, 'month_days': 31, 'monthly': 999}, [2000, 2, 2]), ('partial-repair probe', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('partial-repair probe', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('normal control', {'annual': 12000, 'months_used': 10, 'days_into_month': 0, 'month_days': 30, 'monthly': 12900}, [2000, 0, 2000]), ('normal control', {'annual': 99900, 'months_used': 0, 'days_into_month': 0, 'month_days': 30, 'monthly': 38952}, [99900, 2, 21996]), ('normal control', {'annual': 119900, 'months_used': 2, 'days_into_month': 0, 'month_days': 31, 'monthly': 1000}, [99916, 99, 916]), ('normal control', {'annual': 12000, 'months_used': 12, 'days_into_month': 15, 'month_days': 30, 'monthly': 999}, [0, 0, 0])], [('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('regression', {'annual': 119900, 'months_used': 4, 'days_into_month': 1, 'month_days': 30, 'monthly': 999}, [69941, 70, 11]), ('partial-repair probe', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('partial-repair probe', {'annual': 422066, 'months_used': 1, 'days_into_month': 1, 'month_days': 31, 'monthly': 1000}, [351721, 351, 721]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 26, 'month_days': 30, 'monthly': 999}, [0, 0, 0]), ('normal control', {'annual': 99900, 'months_used': 13, 'days_into_month': 0, 'month_days': 30, 'monthly': 27694}, [0, 0, 0]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 10, 'month_days': 28, 'monthly': 9029}, [0, 0, 0]), ('normal control', {'annual': 12000, 'months_used': 4, 'days_into_month': 0, 'month_days': 28, 'monthly': 999}, [8000, 8, 8])], [('regression', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 16, 'month_days': 28, 'monthly': 12900}, [66600, 5, 2100]), ('partial-repair probe', {'annual': 228567, 'months_used': 5, 'days_into_month': 1, 'month_days': 31, 'monthly': 12900}, [114283, 8, 11083]), ('partial-repair probe', {'annual': 99900, 'months_used': 2, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [74925, 74, 925]), ('normal control', {'annual': 119900, 'months_used': 7, 'days_into_month': 0, 'month_days': 30, 'monthly': 39814}, [49958, 1, 10144]), ('normal control', {'annual': 99900, 'months_used': 6, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [49950, 50, 0]), ('normal control', {'annual': 177114, 'months_used': 10, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [29519, 29, 548]), ('normal control', {'annual': 238019, 'months_used': 5, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [138844, 138, 982])], [('regression', {'annual': 422066, 'months_used': 1, 'days_into_month': 1, 'month_days': 31, 'monthly': 1000}, [351721, 351, 721]), ('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('partial-repair probe', {'annual': 99900, 'months_used': 9, 'days_into_month': 15, 'month_days': 30, 'monthly': 23011}, [16650, 0, 16650]), ('partial-repair probe', {'annual': 12000, 'months_used': 6, 'days_into_month': 2, 'month_days': 31, 'monthly': 12900}, [5000, 0, 5000]), ('normal control', {'annual': 119900, 'months_used': 13, 'days_into_month': 16, 'month_days': 28, 'monthly': 999}, [0, 0, 0]), ('normal control', {'annual': 12000, 'months_used': 12, 'days_into_month': 16, 'month_days': 28, 'monthly': 20303}, [0, 0, 0]), ('normal control', {'annual': 119900, 'months_used': 5, 'days_into_month': 0, 'month_days': 30, 'monthly': 10366}, [69941, 6, 7745]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 16, 'month_days': 28, 'monthly': 12900}, [0, 0, 0])], [('regression', {'annual': 228567, 'months_used': 5, 'days_into_month': 1, 'month_days': 31, 'monthly': 12900}, [114283, 8, 11083]), ('regression', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('partial-repair probe', {'annual': 119900, 'months_used': 5, 'days_into_month': 1, 'month_days': 28, 'monthly': 999}, [59950, 60, 10]), ('partial-repair probe', {'annual': 68414, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 999}, [5701, 5, 706]), ('normal control', {'annual': 135833, 'months_used': 9, 'days_into_month': 0, 'month_days': 28, 'monthly': 12900}, [33958, 2, 8158]), ('normal control', {'annual': 99900, 'months_used': 13, 'days_into_month': 15, 'month_days': 30, 'monthly': 12900}, [0, 0, 0]), ('normal control', {'annual': 425201, 'months_used': 11, 'days_into_month': 0, 'month_days': 31, 'monthly': 12900}, [35433, 2, 9633]), ('normal control', {'annual': 119900, 'months_used': 11, 'days_into_month': 0, 'month_days': 28, 'monthly': 999}, [9991, 10, 1])]]\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":"b05b3a5ff8d6886a30aabbb4f7a8d16493e0427961c8ca4d20c3c64814c82608","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    started = x['months_used'] + 0\n    started = min(started, 12)\n    credit = x['annual'] * (12 - started) // 12\n    covered = credit // x['monthly']\n    left = credit - covered * x['monthly']\n    return [credit, covered, left]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'annual': 119900, 'months_used': 4, 'days_into_month': 1, 'month_days': 30, 'monthly': 999}, [69941, 70, 11]), ('regression', {'annual': 12000, 'months_used': 9, 'days_into_month': 16, 'month_days': 31, 'monthly': 999}, [2000, 2, 2]), ('partial-repair probe', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('partial-repair probe', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('normal control', {'annual': 12000, 'months_used': 10, 'days_into_month': 0, 'month_days': 30, 'monthly': 12900}, [2000, 0, 2000]), ('normal control', {'annual': 99900, 'months_used': 0, 'days_into_month': 0, 'month_days': 30, 'monthly': 38952}, [99900, 2, 21996]), ('normal control', {'annual': 119900, 'months_used': 2, 'days_into_month': 0, 'month_days': 31, 'monthly': 1000}, [99916, 99, 916]), ('normal control', {'annual': 12000, 'months_used': 12, 'days_into_month': 15, 'month_days': 30, 'monthly': 999}, [0, 0, 0])], [('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('regression', {'annual': 119900, 'months_used': 4, 'days_into_month': 1, 'month_days': 30, 'monthly': 999}, [69941, 70, 11]), ('partial-repair probe', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('partial-repair probe', {'annual': 422066, 'months_used': 1, 'days_into_month': 1, 'month_days': 31, 'monthly': 1000}, [351721, 351, 721]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 26, 'month_days': 30, 'monthly': 999}, [0, 0, 0]), ('normal control', {'annual': 99900, 'months_used': 13, 'days_into_month': 0, 'month_days': 30, 'monthly': 27694}, [0, 0, 0]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 10, 'month_days': 28, 'monthly': 9029}, [0, 0, 0]), ('normal control', {'annual': 12000, 'months_used': 4, 'days_into_month': 0, 'month_days': 28, 'monthly': 999}, [8000, 8, 8])], [('regression', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 16, 'month_days': 28, 'monthly': 12900}, [66600, 5, 2100]), ('partial-repair probe', {'annual': 228567, 'months_used': 5, 'days_into_month': 1, 'month_days': 31, 'monthly': 12900}, [114283, 8, 11083]), ('partial-repair probe', {'annual': 99900, 'months_used': 2, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [74925, 74, 925]), ('normal control', {'annual': 119900, 'months_used': 7, 'days_into_month': 0, 'month_days': 30, 'monthly': 39814}, [49958, 1, 10144]), ('normal control', {'annual': 99900, 'months_used': 6, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [49950, 50, 0]), ('normal control', {'annual': 177114, 'months_used': 10, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [29519, 29, 548]), ('normal control', {'annual': 238019, 'months_used': 5, 'days_into_month': 0, 'month_days': 30, 'monthly': 999}, [138844, 138, 982])], [('regression', {'annual': 422066, 'months_used': 1, 'days_into_month': 1, 'month_days': 31, 'monthly': 1000}, [351721, 351, 721]), ('regression', {'annual': 99900, 'months_used': 3, 'days_into_month': 1, 'month_days': 31, 'monthly': 16870}, [66600, 3, 15990]), ('partial-repair probe', {'annual': 99900, 'months_used': 9, 'days_into_month': 15, 'month_days': 30, 'monthly': 23011}, [16650, 0, 16650]), ('partial-repair probe', {'annual': 12000, 'months_used': 6, 'days_into_month': 2, 'month_days': 31, 'monthly': 12900}, [5000, 0, 5000]), ('normal control', {'annual': 119900, 'months_used': 13, 'days_into_month': 16, 'month_days': 28, 'monthly': 999}, [0, 0, 0]), ('normal control', {'annual': 12000, 'months_used': 12, 'days_into_month': 16, 'month_days': 28, 'monthly': 20303}, [0, 0, 0]), ('normal control', {'annual': 119900, 'months_used': 5, 'days_into_month': 0, 'month_days': 30, 'monthly': 10366}, [69941, 6, 7745]), ('normal control', {'annual': 119900, 'months_used': 12, 'days_into_month': 16, 'month_days': 28, 'monthly': 12900}, [0, 0, 0])], [('regression', {'annual': 228567, 'months_used': 5, 'days_into_month': 1, 'month_days': 31, 'monthly': 12900}, [114283, 8, 11083]), ('regression', {'annual': 99900, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 1000}, [8325, 8, 325]), ('partial-repair probe', {'annual': 119900, 'months_used': 5, 'days_into_month': 1, 'month_days': 28, 'monthly': 999}, [59950, 60, 10]), ('partial-repair probe', {'annual': 68414, 'months_used': 10, 'days_into_month': 15, 'month_days': 31, 'monthly': 999}, [5701, 5, 706]), ('normal control', {'annual': 135833, 'months_used': 9, 'days_into_month': 0, 'month_days': 28, 'monthly': 12900}, [33958, 2, 8158]), ('normal control', {'annual': 99900, 'months_used': 13, 'days_into_month': 15, 'month_days': 30, 'monthly': 12900}, [0, 0, 0]), ('normal control', {'annual': 425201, 'months_used': 11, 'days_into_month': 0, 'month_days': 31, 'monthly': 12900}, [35433, 2, 9633]), ('normal control', {'annual': 119900, 'months_used': 11, 'days_into_month': 0, 'month_days': 28, 'monthly': 999}, [9991, 10, 1])]]\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-annual-to-monthly-credit-partial-month-counted-as-used","generated_at":"2026-09-29T14:46:37.231391+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Switching billing intervals converts unused prepaid time into credit that funds future invoices.","root_cause":"The current partially used month is treated as unused.","sha256":"d236fdd1871521db1bdecf4e8a5a35ba7588671fed648a53a60c54582e8bcea1","title":"Annual-to-monthly switch credit: partial month counted as used · 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":41.846,"exit_code":1,"observations":[{"actual":[79933,80,13],"check":"regression 0","expected":[69941,70,11],"passed":false},{"actual":[2000,2,2],"check":"regression 1","expected":[2000,2,2],"passed":true},{"actual":[74925,4,7445],"check":"partial-repair probe 2","expected":[66600,3,15990],"passed":false},{"actual":[16650,16,650],"check":"partial-repair probe 3","expected":[8325,8,325],"passed":false},{"actual":[2000,0,2000],"check":"normal control 4","expected":[2000,0,2000],"passed":true},{"actual":[99900,2,21996],"check":"normal control 5","expected":[99900,2,21996],"passed":true},{"actual":[99916,99,916],"check":"normal control 6","expected":[99916,99,916],"passed":true},{"actual":[0,0,0],"check":"normal control 7","expected":[0,0,0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [79933, 80, 13], \"expected\": [69941, 70, 11], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [2000, 2, 2], \"expected\": [2000, 2, 2], \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": [74925, 4, 7445], \"expected\": [66600, 3, 15990], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [16650, 16, 650], \"expected\": [8325, 8, 325], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [2000, 0, 2000], \"expected\": [2000, 0, 2000], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [99900, 2, 21996], \"expected\": [99900, 2, 21996], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [99916, 99, 916], \"expected\": [99916, 99, 916], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [0, 0, 0], \"expected\": [0, 0, 0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.727,"exit_code":1,"observations":[{"actual":[79933,80,13],"check":"regression 0","expected":[69941,70,11],"passed":false},{"actual":[3000,3,3],"check":"regression 1","expected":[2000,2,2],"passed":false},{"actual":[74925,4,7445],"check":"partial-repair probe 2","expected":[66600,3,15990],"passed":false},{"actual":[16650,16,650],"check":"partial-repair probe 3","expected":[8325,8,325],"passed":false},{"actual":[2000,0,2000],"check":"normal control 4","expected":[2000,0,2000],"passed":true},{"actual":[99900,2,21996],"check":"normal control 5","expected":[99900,2,21996],"passed":true},{"actual":[99916,99,916],"check":"normal control 6","expected":[99916,99,916],"passed":true},{"actual":[0,0,0],"check":"normal control 7","expected":[0,0,0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [79933, 80, 13], \"expected\": [69941, 70, 11], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [3000, 3, 3], \"expected\": [2000, 2, 2], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [74925, 4, 7445], \"expected\": [66600, 3, 15990], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [16650, 16, 650], \"expected\": [8325, 8, 325], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [2000, 0, 2000], \"expected\": [2000, 0, 2000], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [99900, 2, 21996], \"expected\": [99900, 2, 21996], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [99916, 99, 916], \"expected\": [99916, 99, 916], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [0, 0, 0], \"expected\": [0, 0, 0], \"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."}}