FA-59476 / Subscription proration billing / Open access
Cancellation refund for unused days: minimum charge term · case 01
Customers cancelling in the first days get refunds exceeding the minimum-charge terms.
ROOT CAUSE
The minimum charged days are ignored.
VERIFIED REPAIR
Restore the contract rule at the minimum charge term step: use `charged_days = max(x['used_days'], x['min_days'])`.
Unsuccessful approach: The attempt adds the minimum to the used days instead of taking the larger.
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, unused]
charged_days = x['used_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': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('normal control', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24])], [('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('partial-repair probe', {'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': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('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': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('partial-repair probe', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('partial-repair probe', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68])], [('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('regression', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0]), ('partial-repair probe', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83])], [('regression', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 13, 'min_days': 14, 'mode': 'immediate'}, [532, 0]), ('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('partial-repair probe', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 365, 'used_days': 323, 'min_days': 7, 'mode': 'period_end'}, [0, 42]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 30, 'used_days': 27, 'min_days': 0, 'mode': 'period_end'}, [0, 3]), ('normal control', {'price': 92433, 'setup': 0, 'period_days': 90, 'used_days': 5, 'min_days': 30, 'mode': 'period_end'}, [0, 85])]]
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 | [4845, 0] | [4518, 0] | Failed |
| regression 1 | [4970, 0] | [4583, 0] | Failed |
| partial-repair probe 2 | [399, 0] | [399, 0] | Passed |
| partial-repair probe 3 | [31973, 0] | [31973, 0] | Passed |
| normal control 4 | [0, 18] | [0, 18] | Passed |
| normal control 5 | [0, 65] | [0, 65] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [0, 24] | [0, 24] | Passed |
SHA-256 / d481aa09bf846ccc7e42292364c1d30969a40ede70da642db7a4db41d9a6689e
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, unused]
charged_days = 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': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('normal control', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24])], [('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('partial-repair probe', {'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': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('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': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('partial-repair probe', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('partial-repair probe', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68])], [('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('regression', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0]), ('partial-repair probe', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83])], [('regression', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 13, 'min_days': 14, 'mode': 'immediate'}, [532, 0]), ('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('partial-repair probe', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 365, 'used_days': 323, 'min_days': 7, 'mode': 'period_end'}, [0, 42]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 30, 'used_days': 27, 'min_days': 0, 'mode': 'period_end'}, [0, 3]), ('normal control', {'price': 92433, 'setup': 0, 'period_days': 90, 'used_days': 5, 'min_days': 30, 'mode': 'period_end'}, [0, 85])]]
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 | [4464, 0] | [4518, 0] | Failed |
| regression 1 | [4583, 0] | [4583, 0] | Passed |
| partial-repair probe 2 | [0, 0] | [399, 0] | Failed |
| partial-repair probe 3 | [0, 0] | [31973, 0] | Failed |
| normal control 4 | [0, 18] | [0, 18] | Passed |
| normal control 5 | [0, 65] | [0, 65] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [0, 24] | [0, 24] | Passed |
SHA-256 / 04f9544b7c16373e70ac0c3f279033d72b4016c5852c9cdc7a380cb403c31227
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': 2500, 'period_days': 90, 'used_days': 1, 'min_days': 7, 'mode': 'immediate'}, [4518, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 18, 'min_days': 14, 'mode': 'immediate'}, [399, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('normal control', {'price': 4900, 'setup': 9483, 'period_days': 31, 'used_days': 13, 'min_days': 0, 'mode': 'period_end'}, [0, 18]), ('normal control', {'price': 32440, 'setup': 0, 'period_days': 90, 'used_days': 25, 'min_days': 14, 'mode': 'period_end'}, [0, 65]), ('normal control', {'price': 28584, 'setup': 2500, 'period_days': 90, 'used_days': 93, 'min_days': 14, 'mode': 'immediate'}, [0, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 66, 'min_days': 0, 'mode': 'period_end'}, [0, 24])], [('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('regression', {'price': 4970, 'setup': 0, 'period_days': 90, 'used_days': 0, 'min_days': 7, 'mode': 'immediate'}, [4583, 0]), ('partial-repair probe', {'price': 119900, 'setup': 0, 'period_days': 30, 'used_days': 22, 'min_days': 14, 'mode': 'immediate'}, [31973, 0]), ('partial-repair probe', {'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': 365, 'used_days': 45, 'min_days': 30, 'mode': 'period_end'}, [0, 320]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'period_end'}, [0, 21]), ('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': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('regression', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('partial-repair probe', {'price': 93530, 'setup': 0, 'period_days': 30, 'used_days': 29, 'min_days': 14, 'mode': 'immediate'}, [3117, 0]), ('partial-repair probe', {'price': 4900, 'setup': 1208, 'period_days': 365, 'used_days': 78, 'min_days': 14, 'mode': 'immediate'}, [3852, 0]), ('normal control', {'price': 999, 'setup': 2500, 'period_days': 31, 'used_days': 16, 'min_days': 0, 'mode': 'immediate'}, [483, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 31, 'used_days': 17, 'min_days': 14, 'mode': 'period_end'}, [0, 14]), ('normal control', {'price': 4900, 'setup': 2500, 'period_days': 365, 'used_days': 232, 'min_days': 0, 'mode': 'immediate'}, [1785, 0]), ('normal control', {'price': 119900, 'setup': 0, 'period_days': 90, 'used_days': 22, 'min_days': 7, 'mode': 'period_end'}, [0, 68])], [('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('regression', {'price': 4900, 'setup': 6691, 'period_days': 31, 'used_days': 19, 'min_days': 30, 'mode': 'immediate'}, [158, 0]), ('partial-repair probe', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 53, 'min_days': 30, 'mode': 'immediate'}, [2014, 0]), ('partial-repair probe', {'price': 119900, 'setup': 1279, 'period_days': 30, 'used_days': 14, 'min_days': 7, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 90, 'used_days': 55, 'min_days': 14, 'mode': 'period_end'}, [0, 35]), ('normal control', {'price': 999, 'setup': 0, 'period_days': 90, 'used_days': 3, 'min_days': 14, 'mode': 'period_end'}, [0, 87]), ('normal control', {'price': 4900, 'setup': 7, 'period_days': 90, 'used_days': 46, 'min_days': 0, 'mode': 'immediate'}, [2395, 0]), ('normal control', {'price': 119900, 'setup': 5059, 'period_days': 90, 'used_days': 7, 'min_days': 0, 'mode': 'period_end'}, [0, 83])], [('regression', {'price': 999, 'setup': 2500, 'period_days': 30, 'used_days': 13, 'min_days': 14, 'mode': 'immediate'}, [532, 0]), ('regression', {'price': 67850, 'setup': 0, 'period_days': 31, 'used_days': 10, 'min_days': 30, 'mode': 'immediate'}, [2188, 0]), ('partial-repair probe', {'price': 119900, 'setup': 3409, 'period_days': 31, 'used_days': 27, 'min_days': 7, 'mode': 'immediate'}, [15470, 0]), ('partial-repair probe', {'price': 119900, 'setup': 2500, 'period_days': 30, 'used_days': 6, 'min_days': 14, 'mode': 'immediate'}, [63946, 0]), ('normal control', {'price': 24966, 'setup': 5091, 'period_days': 31, 'used_days': 26, 'min_days': 0, 'mode': 'immediate'}, [4026, 0]), ('normal control', {'price': 119900, 'setup': 2500, 'period_days': 365, 'used_days': 323, 'min_days': 7, 'mode': 'period_end'}, [0, 42]), ('normal control', {'price': 4900, 'setup': 0, 'period_days': 30, 'used_days': 27, 'min_days': 0, 'mode': 'period_end'}, [0, 3]), ('normal control', {'price': 92433, 'setup': 0, 'period_days': 90, 'used_days': 5, 'min_days': 30, 'mode': 'period_end'}, [0, 85])]]
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 | [4518, 0] | [4518, 0] | Passed |
| regression 1 | [4583, 0] | [4583, 0] | Passed |
| partial-repair probe 2 | [399, 0] | [399, 0] | Passed |
| partial-repair probe 3 | [31973, 0] | [31973, 0] | Passed |
| normal control 4 | [0, 18] | [0, 18] | Passed |
| normal control 5 | [0, 65] | [0, 65] | Passed |
| normal control 6 | [0, 0] | [0, 0] | Passed |
| normal control 7 | [0, 24] | [0, 24] | Passed |
SHA-256 / 94b1e31e17148b67639d3c0bcc3a17a7527dc70dc63cffe6ad3189191cc73b31
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 2026-09-29T14:46:36.733324+00:00.
Case digest / 8bca58ee1c208d6b72df108740f8ec4b8b9499311f9f6b8ff9cb678c05fe0442