{"abstract":"Removing seats mid-cycle reduces the invoice although the contract grants credit only at renewal.","category":"Subscription proration billing","checks":8,"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 credits a full period price for seats dropped below the base count.","family":"w2-subscription-proration-seat-high-water-mark-no-mid-cycle-removal-credit","id":"FA-59406","implementations":{"attempt":{"sha256":"2468f1efeb18b85d4df3d57ac13dfe157e02d6c68b913dfeb7fd86410f4acd52","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])\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        if count < x['base_seats']:\n            charge -= x['price'] * (x['base_seats'] - 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 (boundary)', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('regression', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('partial-repair probe', {'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': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 8, 'changes': []}, [0, 8, 8]), ('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]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 6, 'changes': [[27, 25], [1, 17], [12, 18]]}, [9143, 25, 25])], [('regression', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('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': 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': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('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]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 7, 'changes': []}, [0, 7, 7]), ('normal control', {'price': 1200, 'period_days': 30, 'base_seats': 13, 'changes': []}, [0, 13, 13])], [('regression', {'price': 1500, 'period_days': 30, 'base_seats': 9, 'changes': [[19, 10], [22, 3], [12, 12], [24, 3], [19, 20]]}, [7100, 20, 3]), ('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': 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': 5820, 'period_days': 365, 'base_seats': 15, 'changes': [[14, 25], [190, 23], [339, 10], [22, 7], [14, 1]]}, [55968, 25, 10]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 4, 'changes': [[333, 15], [352, 23], [4, 5]]}, [2581, 23, 23]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 1, 'changes': [[19, 14], [24, 18]]}, [7123, 18, 18])], [('regression', {'price': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('partial-repair probe', {'price': 7507, 'period_days': 31, 'base_seats': 15, 'changes': [[15, 8]]}, [0, 15, 8]), ('partial-repair probe', {'price': 2726, 'period_days': 365, 'base_seats': 15, 'changes': [[171, 14], [284, 12], [141, 18], [171, 5]]}, [5019, 18, 12]), ('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]), ('normal control', {'price': 1200, 'period_days': 28, 'base_seats': 9, 'changes': []}, [0, 9, 9])], [('regression', {'price': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('partial-repair probe', {'price': 800, 'period_days': 31, 'base_seats': 7, 'changes': [[14, 11], [13, 12], [19, 0], [30, 25], [23, 8]]}, [2658, 25, 25]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 2, 'changes': [[26, 6], [4, 0], [26, 2]]}, [429, 6, 2]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 2, 'changes': [[3, 10]]}, [8671, 10, 10]), ('normal control', {'price': 8587, 'period_days': 30, 'base_seats': 12, 'changes': []}, [0, 12, 12]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 8445, 'period_days': 365, 'base_seats': 1, 'changes': [[278, 2], [278, 7]]}, [12078, 7, 7])]]\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":"2e8d5753b4a2b5ba3ba0b97ec660ce00aa0f3b04a24c2b1e148fa0caa6829ed7","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])\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        if count < current:\n            charge -= (x['price'] * (current - count) * (x['period_days'] - day) * 2 + x['period_days']) // (2 * x['period_days'])\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 (boundary)', {'price': 1000, 'period_days': 30, 'base_seats': 5, 'changes': [[3, 3], [10, 5], [12, 7]]}, [1200, 7, 7]), ('regression', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('partial-repair probe', {'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': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('normal control', {'price': 800, 'period_days': 31, 'base_seats': 8, 'changes': []}, [0, 8, 8]), ('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]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 6, 'changes': [[27, 25], [1, 17], [12, 18]]}, [9143, 25, 25])], [('regression', {'price': 800, 'period_days': 30, 'base_seats': 13, 'changes': [[15, 1]]}, [0, 13, 1]), ('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': 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': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('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]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 7, 'changes': []}, [0, 7, 7]), ('normal control', {'price': 1200, 'period_days': 30, 'base_seats': 13, 'changes': []}, [0, 13, 13])], [('regression', {'price': 1500, 'period_days': 30, 'base_seats': 9, 'changes': [[19, 10], [22, 3], [12, 12], [24, 3], [19, 20]]}, [7100, 20, 3]), ('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': 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': 5820, 'period_days': 365, 'base_seats': 15, 'changes': [[14, 25], [190, 23], [339, 10], [22, 7], [14, 1]]}, [55968, 25, 10]), ('normal control', {'price': 800, 'period_days': 30, 'base_seats': 1, 'changes': []}, [0, 1, 1]), ('normal control', {'price': 800, 'period_days': 28, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 4, 'changes': [[333, 15], [352, 23], [4, 5]]}, [2581, 23, 23]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 1, 'changes': [[19, 14], [24, 18]]}, [7123, 18, 18])], [('regression', {'price': 1200, 'period_days': 30, 'base_seats': 11, 'changes': [[6, 20], [12, 8], [15, 1], [7, 5], [0, 11]]}, [8640, 20, 1]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('partial-repair probe', {'price': 7507, 'period_days': 31, 'base_seats': 15, 'changes': [[15, 8]]}, [0, 15, 8]), ('partial-repair probe', {'price': 2726, 'period_days': 365, 'base_seats': 15, 'changes': [[171, 14], [284, 12], [141, 18], [171, 5]]}, [5019, 18, 12]), ('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]), ('normal control', {'price': 1200, 'period_days': 28, 'base_seats': 9, 'changes': []}, [0, 9, 9])], [('regression', {'price': 1500, 'period_days': 28, 'base_seats': 12, 'changes': [[0, 4], [0, 9], [6, 24], [23, 1], [9, 21]]}, [14143, 24, 1]), ('regression', {'price': 1500, 'period_days': 28, 'base_seats': 10, 'changes': [[1, 16], [20, 13]]}, [8679, 16, 13]), ('partial-repair probe', {'price': 800, 'period_days': 31, 'base_seats': 7, 'changes': [[14, 11], [13, 12], [19, 0], [30, 25], [23, 8]]}, [2658, 25, 25]), ('partial-repair probe', {'price': 1500, 'period_days': 28, 'base_seats': 2, 'changes': [[26, 6], [4, 0], [26, 2]]}, [429, 6, 2]), ('normal control', {'price': 1200, 'period_days': 31, 'base_seats': 2, 'changes': [[3, 10]]}, [8671, 10, 10]), ('normal control', {'price': 8587, 'period_days': 30, 'base_seats': 12, 'changes': []}, [0, 12, 12]), ('normal control', {'price': 1200, 'period_days': 365, 'base_seats': 11, 'changes': []}, [0, 11, 11]), ('normal control', {'price': 8445, 'period_days': 365, 'base_seats': 1, 'changes': [[278, 2], [278, 7]]}, [12078, 7, 7])]]\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-no-mid-cycle-removal-credit","generated_at":"2026-09-29T14:46:36.062171+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":"Seat decreases generate prorated credits.","sha256":"b237c283e010208a097489c83048c077f5ab573c8d40aaff01f4d2a31927d134","title":"Seat additions billed above the high-water mark: no mid-cycle removal credit · 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":42.29,"exit_code":1,"observations":[{"actual":[-800,7,7],"check":"regression (boundary) 0","expected":[1200,7,7],"passed":false},{"actual":[-9600,13,1],"check":"regression 1","expected":[0,13,1],"passed":false},{"actual":[-10900,20,3],"check":"partial-repair probe 2","expected":[7100,20,3],"passed":false},{"actual":[-14160,20,1],"check":"partial-repair probe 3","expected":[8640,20,1],"passed":false},{"actual":[0,8,8],"check":"normal control 4","expected":[0,8,8],"passed":true},{"actual":[0,11,11],"check":"normal control 5","expected":[0,11,11],"passed":true},{"actual":[0,12,12],"check":"normal control 6","expected":[0,12,12],"passed":true},{"actual":[9143,25,25],"check":"normal control 7","expected":[9143,25,25],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression (boundary) 0\", \"actual\": [-800, 7, 7], \"expected\": [1200, 7, 7], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [-9600, 13, 1], \"expected\": [0, 13, 1], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [-10900, 20, 3], \"expected\": [7100, 20, 3], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [-14160, 20, 1], \"expected\": [8640, 20, 1], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [0, 8, 8], \"expected\": [0, 8, 8], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [0, 11, 11], \"expected\": [0, 11, 11], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [0, 12, 12], \"expected\": [0, 12, 12], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [9143, 25, 25], \"expected\": [9143, 25, 25], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":44.84,"exit_code":1,"observations":[{"actual":[-600,7,7],"check":"regression (boundary) 0","expected":[1200,7,7],"passed":false},{"actual":[-4800,13,1],"check":"regression 1","expected":[0,13,1],"passed":false},{"actual":[-800,20,3],"check":"partial-repair probe 2","expected":[7100,20,3],"passed":false},{"actual":[-9360,20,1],"check":"partial-repair probe 3","expected":[8640,20,1],"passed":false},{"actual":[0,8,8],"check":"normal control 4","expected":[0,8,8],"passed":true},{"actual":[0,11,11],"check":"normal control 5","expected":[0,11,11],"passed":true},{"actual":[0,12,12],"check":"normal control 6","expected":[0,12,12],"passed":true},{"actual":[9143,25,25],"check":"normal control 7","expected":[9143,25,25],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression (boundary) 0\", \"actual\": [-600, 7, 7], \"expected\": [1200, 7, 7], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [-4800, 13, 1], \"expected\": [0, 13, 1], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [-800, 20, 3], \"expected\": [7100, 20, 3], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [-9360, 20, 1], \"expected\": [8640, 20, 1], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [0, 8, 8], \"expected\": [0, 8, 8], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [0, 11, 11], \"expected\": [0, 11, 11], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [0, 12, 12], \"expected\": [0, 12, 12], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [9143, 25, 25], \"expected\": [9143, 25, 25], \"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."}}