{"abstract":"Out-of-order change logs charge seats for the wrong number of days.","category":"Subscription proration billing","checks":9,"contract":"Input {price per seat per period, period_days, base_seats, changes: [[day, seat_count]]}. Changes apply in day order (same-day changes keep input order). Seats above the period high-water mark are charged price*added*(period_days - day)/period_days half-up; decreases earn no mid-cycle credit. Return [prorated charges, high-water mark, renewal seat count (the last count)].","contract_signature":"x","evaluation_group":"w2-subscription-proration-seat-high-water-mark","failed_approach":"The attempt sorts by day but breaks same-day ties by seat count instead of input order.","family":"w2-subscription-proration-seat-high-water-mark-chronological-change-order","id":"FA-59411","implementations":{"attempt":{"sha256":"f0ff655f5ef021b6770422585e5661389c09841392843c58fd06620b377ea0dc","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    ch = sorted(x['changes'], key=lambda c: (c[0], c[1]))\n    hwm = current = x['base_seats']\n    charge = 0\n    for day, count in ch:\n        if count > hwm:\n            added = count - hwm\n            left = x['period_days'] - day\n            charge += (x['price'] * added * left * 2 + x['period_days']) // (2 * x['period_days'])\n            hwm = count\n        current = count\n    final = ch[-1][1] if ch else x['base_seats']\n    return [charge, hwm, final]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'price': 800, 'period_days': 30, 'base_seats': 11, 'changes': [[20, 22], [5, 15], [20, 14]]}, [4534, 22, 14]), ('regression', {'price': 1500, 'period_days': 30, 'base_seats': 9, 'changes': [[19, 10], [22, 3], [12, 12], [24, 3], [19, 20]]}, [7100, 20, 3]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 2, 'changes': [[26, 6], [4, 0], [26, 2]]}, [429, 6, 2]), ('partial-repair probe', {'price': 1200, 'period_days': 30, 'base_seats': 5, 'changes': [[22, 12], [22, 9]]}, [2240, 12, 9]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 8, 'changes': []}, [0, 8, 8]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 5360, 'period_days': 28, 'base_seats': 12, 'changes': []}, [0, 12, 12])], [('regression', {'price': 800, 'period_days': 28, 'base_seats': 1, 'changes': [[8, 6], [20, 16], [14, 24], [20, 8], [8, 18]]}, [12114, 24, 8]), ('regression', {'price': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('partial-repair probe', {'price': 1200, 'period_days': 30, 'base_seats': 5, 'changes': [[22, 12], [22, 9]]}, [2240, 12, 9]), ('partial-repair probe', {'price': 800, 'period_days': 28, 'base_seats': 12, 'changes': [[10, 22], [10, 5]]}, [5143, 22, 5]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('normal control', {'price': 7507, 'period_days': 31, 'base_seats': 15, 'changes': [[15, 8]]}, [0, 15, 8]), ('normal control', {'price': 1500, 'period_days': 31, 'base_seats': 6, 'changes': []}, [0, 6, 6]), ('normal control', {'price': 800, 'period_days': 365, 'base_seats': 15, 'changes': []}, [0, 15, 15])], [('regression', {'price': 6996, 'period_days': 31, 'base_seats': 1, 'changes': [[20, 25], [20, 21], [14, 19], [5, 9], [20, 18]]}, [100201, 25, 18]), ('regression', {'price': 800, 'period_days': 28, 'base_seats': 6, 'changes': [[27, 25], [1, 17], [12, 18]]}, [9143, 25, 25]), ('partial-repair probe', {'price': 800, 'period_days': 28, 'base_seats': 12, 'changes': [[10, 22], [10, 5]]}, [5143, 22, 5]), ('partial-repair probe', {'price': 800, 'period_days': 31, 'base_seats': 6, 'changes': [[4, 17], [4, 6]]}, [7665, 17, 6]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 7, 'changes': []}, [0, 7, 7]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 9, 'changes': [[0, 4], [4, 7]]}, [0, 9, 7]), ('normal control', {'price': 1200, 'period_days': 30, 'base_seats': 13, 'changes': []}, [0, 13, 13]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 2, 'changes': [[14, 0]]}, [0, 2, 0])], [('regression', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[26, 12], [9, 10], [26, 2], [8, 24], [12, 2], [26, 6]]}, [11733, 24, 6]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 11, 'changes': [[3, 14], [6, 7], [15, 20], [15, 9]]}, [8197, 20, 9]), ('partial-repair probe', {'price': 6996, 'period_days': 31, 'base_seats': 1, 'changes': [[20, 25], [20, 21], [14, 19], [5, 9], [20, 18]]}, [100201, 25, 18]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 1500, 'period_days': 30, 'base_seats': 1, 'changes': [[18, 0], [27, 5]]}, [600, 5, 5]), ('normal control', {'price': 1500, 'period_days': 31, 'base_seats': 13, 'changes': [[24, 7]]}, [0, 13, 7]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 11, 'changes': []}, [0, 11, 11])], [('regression', {'price': 2883, 'period_days': 30, 'base_seats': 5, 'changes': [[21, 11], [0, 6], [21, 10]]}, [7208, 11, 10]), ('regression', {'price': 5820, 'period_days': 365, 'base_seats': 15, 'changes': [[14, 25], [190, 23], [339, 10], [22, 7], [14, 1]]}, [55968, 25, 10]), ('partial-repair probe', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[26, 12], [9, 10], [26, 2], [8, 24], [12, 2], [26, 6]]}, [11733, 24, 6]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 5, 'changes': [[24, 9], [24, 19], [24, 10]]}, [3000, 19, 10]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 1, 'changes': [[19, 14], [24, 18]]}, [7123, 18, 18]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[21, 22], [29, 24]]}, [4373, 24, 24]), ('normal control', {'price': 6240, 'period_days': 28, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 2, 'changes': []}, [0, 2, 2])]]\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":"50a093030d420b770e43e2aa8aa9257b2028a2edfc309a2a2ef37d13fbca5195","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    ch = x['changes']\n    hwm = current = x['base_seats']\n    charge = 0\n    for day, count in ch:\n        if count > hwm:\n            added = count - hwm\n            left = x['period_days'] - day\n            charge += (x['price'] * added * left * 2 + x['period_days']) // (2 * x['period_days'])\n            hwm = count\n        current = count\n    final = ch[-1][1] if ch else x['base_seats']\n    return [charge, hwm, final]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'price': 800, 'period_days': 30, 'base_seats': 11, 'changes': [[20, 22], [5, 15], [20, 14]]}, [4534, 22, 14]), ('regression', {'price': 1500, 'period_days': 30, 'base_seats': 9, 'changes': [[19, 10], [22, 3], [12, 12], [24, 3], [19, 20]]}, [7100, 20, 3]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 2, 'changes': [[26, 6], [4, 0], [26, 2]]}, [429, 6, 2]), ('partial-repair probe', {'price': 1200, 'period_days': 30, 'base_seats': 5, 'changes': [[22, 12], [22, 9]]}, [2240, 12, 9]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 8, 'changes': []}, [0, 8, 8]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 5360, 'period_days': 28, 'base_seats': 12, 'changes': []}, [0, 12, 12])], [('regression', {'price': 800, 'period_days': 28, 'base_seats': 1, 'changes': [[8, 6], [20, 16], [14, 24], [20, 8], [8, 18]]}, [12114, 24, 8]), ('regression', {'price': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('partial-repair probe', {'price': 1200, 'period_days': 30, 'base_seats': 5, 'changes': [[22, 12], [22, 9]]}, [2240, 12, 9]), ('partial-repair probe', {'price': 800, 'period_days': 28, 'base_seats': 12, 'changes': [[10, 22], [10, 5]]}, [5143, 22, 5]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('normal control', {'price': 7507, 'period_days': 31, 'base_seats': 15, 'changes': [[15, 8]]}, [0, 15, 8]), ('normal control', {'price': 1500, 'period_days': 31, 'base_seats': 6, 'changes': []}, [0, 6, 6]), ('normal control', {'price': 800, 'period_days': 365, 'base_seats': 15, 'changes': []}, [0, 15, 15])], [('regression', {'price': 6996, 'period_days': 31, 'base_seats': 1, 'changes': [[20, 25], [20, 21], [14, 19], [5, 9], [20, 18]]}, [100201, 25, 18]), ('regression', {'price': 800, 'period_days': 28, 'base_seats': 6, 'changes': [[27, 25], [1, 17], [12, 18]]}, [9143, 25, 25]), ('partial-repair probe', {'price': 800, 'period_days': 28, 'base_seats': 12, 'changes': [[10, 22], [10, 5]]}, [5143, 22, 5]), ('partial-repair probe', {'price': 800, 'period_days': 31, 'base_seats': 6, 'changes': [[4, 17], [4, 6]]}, [7665, 17, 6]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 7, 'changes': []}, [0, 7, 7]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 9, 'changes': [[0, 4], [4, 7]]}, [0, 9, 7]), ('normal control', {'price': 1200, 'period_days': 30, 'base_seats': 13, 'changes': []}, [0, 13, 13]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 2, 'changes': [[14, 0]]}, [0, 2, 0])], [('regression', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[26, 12], [9, 10], [26, 2], [8, 24], [12, 2], [26, 6]]}, [11733, 24, 6]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 11, 'changes': [[3, 14], [6, 7], [15, 20], [15, 9]]}, [8197, 20, 9]), ('partial-repair probe', {'price': 6996, 'period_days': 31, 'base_seats': 1, 'changes': [[20, 25], [20, 21], [14, 19], [5, 9], [20, 18]]}, [100201, 25, 18]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 1500, 'period_days': 30, 'base_seats': 1, 'changes': [[18, 0], [27, 5]]}, [600, 5, 5]), ('normal control', {'price': 1500, 'period_days': 31, 'base_seats': 13, 'changes': [[24, 7]]}, [0, 13, 7]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 11, 'changes': []}, [0, 11, 11])], [('regression', {'price': 2883, 'period_days': 30, 'base_seats': 5, 'changes': [[21, 11], [0, 6], [21, 10]]}, [7208, 11, 10]), ('regression', {'price': 5820, 'period_days': 365, 'base_seats': 15, 'changes': [[14, 25], [190, 23], [339, 10], [22, 7], [14, 1]]}, [55968, 25, 10]), ('partial-repair probe', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[26, 12], [9, 10], [26, 2], [8, 24], [12, 2], [26, 6]]}, [11733, 24, 6]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 5, 'changes': [[24, 9], [24, 19], [24, 10]]}, [3000, 19, 10]), ('boundary control', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 1, 'changes': [[19, 14], [24, 18]]}, [7123, 18, 18]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 4, 'changes': [[21, 22], [29, 24]]}, [4373, 24, 24]), ('normal control', {'price': 6240, 'period_days': 28, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 2, 'changes': []}, [0, 2, 2])]]\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-seat-high-water-mark-chronological-change-order","generated_at":"2026-09-29T14:46:36.137783+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Seat-based billing charges each seat at most once per period, even when seats are removed and re-added.","root_cause":"Changes are processed in log order rather than by day.","sha256":"2a9fd87ad0c3f19c9139bc5747d26381a4ce4c6dc2e54155ff23d3547726ce16","title":"Seat additions billed above the high-water mark: chronological change order · 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":40.685,"exit_code":1,"observations":[{"actual":[4534,22,22],"check":"regression 0","expected":[4534,22,14],"passed":false},{"actual":[7100,20,3],"check":"regression 1","expected":[7100,20,3],"passed":true},{"actual":[429,6,6],"check":"partial-repair probe 2","expected":[429,6,2],"passed":false},{"actual":[2240,12,12],"check":"partial-repair probe 3","expected":[2240,12,9],"passed":false},{"actual":[1200,7,7],"check":"boundary control 4","expected":[1200,7,7],"passed":true},{"actual":[0,8,8],"check":"normal control 5","expected":[0,8,8],"passed":true},{"actual":[0,13,1],"check":"normal control 6","expected":[0,13,1],"passed":true},{"actual":[0,11,11],"check":"normal control 7","expected":[0,11,11],"passed":true},{"actual":[0,12,12],"check":"normal control 8","expected":[0,12,12],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [4534, 22, 22], \"expected\": [4534, 22, 14], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [7100, 20, 3], \"expected\": [7100, 20, 3], \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": [429, 6, 6], \"expected\": [429, 6, 2], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [2240, 12, 12], \"expected\": [2240, 12, 9], \"passed\": false}, {\"check\": \"boundary control 4\", \"actual\": [1200, 7, 7], \"expected\": [1200, 7, 7], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [0, 8, 8], \"expected\": [0, 8, 8], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [0, 13, 1], \"expected\": [0, 13, 1], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [0, 11, 11], \"expected\": [0, 11, 11], \"passed\": true}, {\"check\": \"normal control 8\", \"actual\": [0, 12, 12], \"expected\": [0, 12, 12], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.749,"exit_code":1,"observations":[{"actual":[2933,22,14],"check":"regression 0","expected":[4534,22,14],"passed":false},{"actual":[6750,20,20],"check":"regression 1","expected":[7100,20,3],"passed":false},{"actual":[429,6,2],"check":"partial-repair probe 2","expected":[429,6,2],"passed":true},{"actual":[2240,12,9],"check":"partial-repair probe 3","expected":[2240,12,9],"passed":true},{"actual":[1200,7,7],"check":"boundary control 4","expected":[1200,7,7],"passed":true},{"actual":[0,8,8],"check":"normal control 5","expected":[0,8,8],"passed":true},{"actual":[0,13,1],"check":"normal control 6","expected":[0,13,1],"passed":true},{"actual":[0,11,11],"check":"normal control 7","expected":[0,11,11],"passed":true},{"actual":[0,12,12],"check":"normal control 8","expected":[0,12,12],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [2933, 22, 14], \"expected\": [4534, 22, 14], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [6750, 20, 20], \"expected\": [7100, 20, 3], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [429, 6, 2], \"expected\": [429, 6, 2], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [2240, 12, 9], \"expected\": [2240, 12, 9], \"passed\": true}, {\"check\": \"boundary control 4\", \"actual\": [1200, 7, 7], \"expected\": [1200, 7, 7], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [0, 8, 8], \"expected\": [0, 8, 8], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [0, 13, 1], \"expected\": [0, 13, 1], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [0, 11, 11], \"expected\": [0, 11, 11], \"passed\": true}, {\"check\": \"normal control 8\", \"actual\": [0, 12, 12], \"expected\": [0, 12, 12], \"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."}}