FA-59826 / Subscription proration billing / Open access
Unused-time credit based on amount paid: credit basis · case 01
Customers who paid with a discount receive credits at the full list price.
ROOT CAUSE
The credit is based on the list price rather than the amount paid.
VERIFIED REPAIR
Restore the contract rule at the credit basis step: use `x['paid'] * x['left'] * 2`.
Unsuccessful approach: The attempt floors the basis at half the list price, still over-crediting heavily discounted periods.
Case contract
Input {list, paid, status paid|partial|open|void|refunded, left, period}. Open, void and refunded invoices earn no unused-time credit. Paid and partially paid invoices earn paid*left/period half-up (the amount actually collected, not the list price). Return cents.
Why this case matters
Credits for unused time must not exceed what the customer actually paid for the period.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
if x['status'] in ('open', 'void', 'refunded'):
return 0
return (x['list'] * x['left'] * 2 + x['period']) // (2 * x['period'])
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('regression', {'list': 4900, 'paid': 2450, 'status': 'partial', 'left': 24, 'period': 31}, 1897), ('partial-repair probe', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4950, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 0, 'status': 'open', 'left': 4, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('regression', {'list': 4900, 'paid': 2450, 'status': 'paid', 'left': 6, 'period': 31}, 474), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 19, 'period': 31}, 3003), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 15, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 1, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 9, 'period': 31}, 0)], [('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('partial-repair probe', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 0, 'status': 'paid', 'left': 31, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'void', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'open', 'left': 25, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 4900, 'paid': 1180, 'status': 'paid', 'left': 4, 'period': 31}, 152), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 5, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 2540, 'status': 'open', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 6, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 786, 'status': 'open', 'left': 21, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 0, 'status': 'refunded', 'left': 28, 'period': 31}, 0)], [('regression', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('regression', {'list': 9900, 'paid': 4950, 'status': 'paid', 'left': 25, 'period': 31}, 3992), ('partial-repair probe', {'list': 9900, 'paid': 3829, 'status': 'paid', 'left': 13, 'period': 31}, 1606), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 29, 'period': 31}, 4584), ('normal control', {'list': 1000, 'paid': 461, 'status': 'refunded', 'left': 10, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'refunded', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4739, 'status': 'refunded', 'left': 24, 'period': 31}, 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 | 419 | 0 | Failed |
| regression 1 | 3794 | 1897 | Failed |
| partial-repair probe 2 | 3635 | 694 | Failed |
| partial-repair probe 3 | 97 | 0 | Failed |
| normal control 4 | 0 | 0 | Passed |
| normal control 5 | 0 | 0 | Passed |
| normal control 6 | 0 | 0 | Passed |
| normal control 7 | 0 | 0 | Passed |
SHA-256 / c3fed32413cd0afe195bd0c88d01daead10f2c9f09f1c45b70818fea03a71a47
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
if x['status'] in ('open', 'void', 'refunded'):
return 0
return (max(x['paid'], x['list'] // 2) * x['left'] * 2 + x['period']) // (2 * x['period'])
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('regression', {'list': 4900, 'paid': 2450, 'status': 'partial', 'left': 24, 'period': 31}, 1897), ('partial-repair probe', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4950, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 0, 'status': 'open', 'left': 4, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('regression', {'list': 4900, 'paid': 2450, 'status': 'paid', 'left': 6, 'period': 31}, 474), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 19, 'period': 31}, 3003), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 15, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 1, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 9, 'period': 31}, 0)], [('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('partial-repair probe', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 0, 'status': 'paid', 'left': 31, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'void', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'open', 'left': 25, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 4900, 'paid': 1180, 'status': 'paid', 'left': 4, 'period': 31}, 152), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 5, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 2540, 'status': 'open', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 6, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 786, 'status': 'open', 'left': 21, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 0, 'status': 'refunded', 'left': 28, 'period': 31}, 0)], [('regression', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('regression', {'list': 9900, 'paid': 4950, 'status': 'paid', 'left': 25, 'period': 31}, 3992), ('partial-repair probe', {'list': 9900, 'paid': 3829, 'status': 'paid', 'left': 13, 'period': 31}, 1606), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 29, 'period': 31}, 4584), ('normal control', {'list': 1000, 'paid': 461, 'status': 'refunded', 'left': 10, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'refunded', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4739, 'status': 'refunded', 'left': 24, 'period': 31}, 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 | 210 | 0 | Failed |
| regression 1 | 1897 | 1897 | Passed |
| partial-repair probe 2 | 1818 | 694 | Failed |
| partial-repair probe 3 | 48 | 0 | Failed |
| normal control 4 | 0 | 0 | Passed |
| normal control 5 | 0 | 0 | Passed |
| normal control 6 | 0 | 0 | Passed |
| normal control 7 | 0 | 0 | Passed |
SHA-256 / 8c89c5f021c9102f25ae6929c5991ba4b5603fcbb2eafea04ce6fe498eec76c5
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
if x['status'] in ('open', 'void', 'refunded'):
return 0
return (x['paid'] * x['left'] * 2 + x['period']) // (2 * x['period'])
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('regression', {'list': 4900, 'paid': 2450, 'status': 'partial', 'left': 24, 'period': 31}, 1897), ('partial-repair probe', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4950, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 9, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 0, 'status': 'open', 'left': 4, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('regression', {'list': 4900, 'paid': 2450, 'status': 'paid', 'left': 6, 'period': 31}, 474), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 19, 'period': 31}, 3003), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 15, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 1, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 500, 'status': 'open', 'left': 9, 'period': 31}, 0)], [('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 3, 'period': 31}, 0), ('regression', {'list': 1000, 'paid': 0, 'status': 'partial', 'left': 13, 'period': 31}, 0), ('partial-repair probe', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('partial-repair probe', {'list': 4900, 'paid': 0, 'status': 'paid', 'left': 31, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'open', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'void', 'left': 3, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'open', 'left': 25, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'void', 'left': 29, 'period': 31}, 0)], [('regression', {'list': 4900, 'paid': 311, 'status': 'partial', 'left': 2, 'period': 31}, 20), ('regression', {'list': 4900, 'paid': 935, 'status': 'partial', 'left': 23, 'period': 31}, 694), ('partial-repair probe', {'list': 4900, 'paid': 1180, 'status': 'paid', 'left': 4, 'period': 31}, 152), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 5, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 2540, 'status': 'open', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 0, 'status': 'refunded', 'left': 6, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 786, 'status': 'open', 'left': 21, 'period': 31}, 0), ('normal control', {'list': 1000, 'paid': 0, 'status': 'refunded', 'left': 28, 'period': 31}, 0)], [('regression', {'list': 9900, 'paid': 0, 'status': 'partial', 'left': 9, 'period': 31}, 0), ('regression', {'list': 9900, 'paid': 4950, 'status': 'paid', 'left': 25, 'period': 31}, 3992), ('partial-repair probe', {'list': 9900, 'paid': 3829, 'status': 'paid', 'left': 13, 'period': 31}, 1606), ('partial-repair probe', {'list': 1000, 'paid': 0, 'status': 'paid', 'left': 27, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 4900, 'status': 'paid', 'left': 29, 'period': 31}, 4584), ('normal control', {'list': 1000, 'paid': 461, 'status': 'refunded', 'left': 10, 'period': 31}, 0), ('normal control', {'list': 4900, 'paid': 2450, 'status': 'refunded', 'left': 20, 'period': 31}, 0), ('normal control', {'list': 9900, 'paid': 4739, 'status': 'refunded', 'left': 24, 'period': 31}, 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 | Passed |
| regression 1 | 1897 | 1897 | Passed |
| partial-repair probe 2 | 694 | 694 | Passed |
| partial-repair probe 3 | 0 | 0 | Passed |
| normal control 4 | 0 | 0 | Passed |
| normal control 5 | 0 | 0 | Passed |
| normal control 6 | 0 | 0 | Passed |
| normal control 7 | 0 | 0 | Passed |
SHA-256 / 950df9901717bec1074815bb1cd925682d0c20fd8503b5c60b0611768e807dcc
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 2026-09-29T14:46:39.965184+00:00.
Case digest / 8e991ae187e9fc77cebc8a19070a5b0ef437d225c76604897d74497022172325