FA-59481 / Subscription proration billing / Open access
Cancellation refund for unused days: period-end access · case 01
Customers cancelling at period end lose access immediately.
ROOT CAUSE
The period-end branch reports no remaining access.
VERIFIED REPAIR
Restore the contract rule at the period-end access step: use `return [0, unused]`.
Unsuccessful approach: The attempt grants a full new period of access.
Case contract
Input {price, setup, period_days, used_days, min_days, mode immediate|period_end}. Unused = max(0, period_days - used_days). period_end: no refund, access continues for the unused days. immediate: charged days = max(used_days, min_days); refund = price*max(0, period_days - charged)/period_days floored (never over-refund); the setup fee is never refunded; access ends. Return [refund, access_days].
Why this case matters
Refund math must respect minimum-charge terms and exclude non-refundable fees.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
unused = max(0, x['period_days'] - x['used_days'])
if x['mode'] == 'period_end':
return [0, 0]
charged_days = max(x['used_days'], x['min_days'])
refundable_days = max(0, x['period_days'] - charged_days)
refund = x['price'] * refundable_days // x['period_days']
return [refund, 0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0])], [('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 86963, 'setup': 0, 'period_days': 90, 'used_days': 71, 'min_days': 14, 'mode': 'immediate'}, [18358, 0]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 30, 'used_days': 19, 'min_days': 0, 'mode': 'immediate'}, [366, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 365, 'used_days': 32, 'min_days': 0, 'mode': 'immediate'}, [109388, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0])], [('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('partial-repair probe', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('normal control', {'price': 119900, 'setup': 464, 'period_days': 90, 'used_days': 62, 'min_days': 14, 'mode': 'immediate'}, [37302, 0])]]
for i, (label, args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (label, i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression 0 | [0, 0] | [0, 18] | Failed |
| regression 1 | [0, 0] | [0, 65] | Failed |
| partial-repair probe 2 | [0, 0] | [0, 24] | Failed |
| partial-repair probe 3 | [0, 0] | [0, 320] | Failed |
| normal control 4 | [4518, 0] | [4518, 0] | Passed |
| normal control 5 | [399, 0] | [399, 0] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [4583, 0] | [4583, 0] | Passed |
SHA-256 / 844805c7a7adea7067e18fb5369f275cb028f779d0fd7bb0d6ae96c0dbd75e3e
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
unused = max(0, x['period_days'] - x['used_days'])
if x['mode'] == 'period_end':
return [0, x['period_days']]
charged_days = max(x['used_days'], x['min_days'])
refundable_days = max(0, x['period_days'] - charged_days)
refund = x['price'] * refundable_days // x['period_days']
return [refund, 0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0])], [('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 86963, 'setup': 0, 'period_days': 90, 'used_days': 71, 'min_days': 14, 'mode': 'immediate'}, [18358, 0]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 30, 'used_days': 19, 'min_days': 0, 'mode': 'immediate'}, [366, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 365, 'used_days': 32, 'min_days': 0, 'mode': 'immediate'}, [109388, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0])], [('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('partial-repair probe', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('normal control', {'price': 119900, 'setup': 464, 'period_days': 90, 'used_days': 62, 'min_days': 14, 'mode': 'immediate'}, [37302, 0])]]
for i, (label, args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (label, i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression 0 | [0, 31] | [0, 18] | Failed |
| regression 1 | [0, 90] | [0, 65] | Failed |
| partial-repair probe 2 | [0, 90] | [0, 24] | Failed |
| partial-repair probe 3 | [0, 365] | [0, 320] | Failed |
| normal control 4 | [4518, 0] | [4518, 0] | Passed |
| normal control 5 | [399, 0] | [399, 0] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [4583, 0] | [4583, 0] | Passed |
SHA-256 / 796509dbff45abfab5f2a4fe7128b0489c4139f348312177d121337e9a838ea1
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
unused = max(0, x['period_days'] - x['used_days'])
if x['mode'] == 'period_end':
return [0, unused]
charged_days = max(x['used_days'], x['min_days'])
refundable_days = max(0, x['period_days'] - charged_days)
refund = x['price'] * refundable_days // x['period_days']
return [refund, 0]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0])], [('regression', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 86963, 'setup': 0, 'period_days': 90, 'used_days': 71, 'min_days': 14, 'mode': 'immediate'}, [18358, 0]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 30, 'used_days': 19, 'min_days': 0, 'mode': 'immediate'}, [366, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 365, 'used_days': 32, 'min_days': 0, 'mode': 'immediate'}, [109388, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24]), ('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0])], [('regression', {'price': 999, 'setup': 0, 'period_days': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0])], [('regression', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('partial-repair probe', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('partial-repair probe', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('normal control', {'price': 119900, 'setup': 464, 'period_days': 90, 'used_days': 62, 'min_days': 14, 'mode': 'immediate'}, [37302, 0])]]
for i, (label, args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (label, i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression 0 | [0, 18] | [0, 18] | Passed |
| regression 1 | [0, 65] | [0, 65] | Passed |
| partial-repair probe 2 | [0, 24] | [0, 24] | Passed |
| partial-repair probe 3 | [0, 320] | [0, 320] | Passed |
| normal control 4 | [4518, 0] | [4518, 0] | Passed |
| normal control 5 | [399, 0] | [399, 0] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [4583, 0] | [4583, 0] | Passed |
SHA-256 / 6d2beed01bf73745d94f8be11a970f15ee131d87825056c8cfd11365182bc58f
Verification & scope
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.
Observations recorded using Python 3.12.14 at 2026-09-29T14:46:36.798897+00:00.
Case digest / b7105b83ada0c9c834f2fc5fc95fea6f5421d332466c4bc3b17bddc590ee66a3