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FA-59631 / Subscription proration billing / Open access

Annual plan proration across leap years: range start clip · case 01

Ranges that begin before the term start are billed for days outside the term.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The range start is not clipped to the term start.

VERIFIED REPAIR

Restore the contract rule at the range start clip step: use `f = max(datetime.date(*x['from']), s)`.

Unsuccessful approach: The attempt clips to the day after the term start, dropping the first day.

Case contract

Input {price, start (annual term start), from, to (exclusive)}. The term is [start, same date next year); a Feb 29 start ends on Mar 1. The requested range is clipped to the term; days = max(0, clipped length). Amount = price*days/term_days half-up. Return [term_days, amount].

Why this case matters

Annual terms have 365 or 366 days depending on whether they contain Feb 29, which changes the daily rate.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
import calendar
N = 1
observations = []
def solve(x):
    s = datetime.date(*x['start'])
    try:
        e = s.replace(year=s.year + 1)
    except ValueError:
        e = datetime.date(s.year + 1, 3, 1)
    f = datetime.date(*x['from'])
    t = min(datetime.date(*x['to']), e)
    days = max(0, (t - f).days)
    total = (e - s).days
    return [total, (x['price'] * days * 2 + total) // (2 * total)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 36500, 'start': [2020, 2, 29], 'from': [2020, 2, 18], 'to': [2020, 6, 27]}, [366, 11867]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('normal control', {'price': 119900, 'start': [2022, 1, 5], 'from': [2022, 2, 1], 'to': [2022, 5, 13]}, [365, 33178]), ('normal control', {'price': 617594, 'start': [2024, 4, 7], 'from': [2024, 5, 22], 'to': [2024, 7, 8]}, [365, 79526]), ('normal control', {'price': 36600, 'start': [2023, 6, 28], 'from': [2024, 5, 21], 'to': [2024, 9, 14]}, [366, 3800]), ('normal control', {'price': 36600, 'start': [2024, 1, 24], 'from': [2024, 4, 28], 'to': [2024, 5, 27]}, [366, 2900])], [('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('normal control', {'price': 119900, 'start': [2025, 7, 19], 'from': [2025, 8, 25], 'to': [2026, 1, 13]}, [365, 46318]), ('normal control', {'price': 975972, 'start': [2023, 4, 12], 'from': [2023, 10, 30], 'to': [2024, 1, 23]}, [366, 226660]), ('normal control', {'price': 401416, 'start': [2025, 2, 14], 'from': [2026, 1, 26], 'to': [2026, 2, 15]}, [365, 20896]), ('normal control', {'price': 36500, 'start': [2025, 4, 22], 'from': [2025, 10, 5], 'to': [2026, 2, 9]}, [365, 12700])], [('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('normal control', {'price': 505919, 'start': [2023, 11, 8], 'from': [2024, 5, 2], 'to': [2024, 8, 16]}, [366, 146523]), ('normal control', {'price': 36600, 'start': [2023, 7, 11], 'from': [2024, 5, 20], 'to': [2024, 7, 20]}, [366, 5200]), ('normal control', {'price': 698116, 'start': [2024, 2, 29], 'from': [2024, 7, 12], 'to': [2024, 7, 24]}, [366, 22889]), ('normal control', {'price': 100385, 'start': [2025, 10, 15], 'from': [2026, 10, 7], 'to': [2026, 10, 15]}, [365, 2200])], [('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('partial-repair probe', {'price': 119900, 'start': [2022, 7, 9], 'from': [2022, 6, 29], 'to': [2022, 12, 28]}, [365, 56501]), ('partial-repair probe', {'price': 314599, 'start': [2024, 9, 25], 'from': [2024, 9, 11], 'to': [2024, 11, 27]}, [365, 54301]), ('normal control', {'price': 36600, 'start': [2023, 4, 2], 'from': [2024, 2, 21], 'to': [2024, 5, 8]}, [366, 4100]), ('normal control', {'price': 466996, 'start': [2020, 2, 29], 'from': [2020, 8, 12], 'to': [2020, 11, 7]}, [366, 111007]), ('normal control', {'price': 119900, 'start': [2024, 6, 29], 'from': [2024, 9, 5], 'to': [2025, 3, 15]}, [365, 62742]), ('normal control', {'price': 36600, 'start': [2023, 8, 24], 'from': [2024, 4, 5], 'to': [2024, 5, 29]}, [366, 5400])], [('regression', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 697175, 'start': [2022, 12, 16], 'from': [2022, 12, 13], 'to': [2023, 3, 31]}, [365, 200557]), ('partial-repair probe', {'price': 119900, 'start': [2022, 4, 19], 'from': [2022, 4, 14], 'to': [2022, 5, 7]}, [365, 5913]), ('normal control', {'price': 36600, 'start': [2023, 5, 5], 'from': [2023, 7, 11], 'to': [2023, 7, 15]}, [366, 400]), ('normal control', {'price': 119900, 'start': [2023, 8, 26], 'from': [2023, 12, 8], 'to': [2023, 12, 16]}, [366, 2621]), ('normal control', {'price': 36500, 'start': [2024, 2, 29], 'from': [2025, 1, 6], 'to': [2025, 5, 17]}, [366, 5385]), ('normal control', {'price': 36500, 'start': [2022, 5, 14], 'from': [2022, 8, 4], 'to': [2022, 11, 25]}, [365, 11300])]]
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 fixtureActualExpectedOutcome
regression 0[366, 12964][366, 11867]Failed
regression 1[366, 100][366, 0]Failed
partial-repair probe 2[366, 4388][366, 3092]Failed
partial-repair probe 3[365, 1404][365, 1404]Passed
normal control 4[365, 33178][365, 33178]Passed
normal control 5[365, 79526][365, 79526]Passed
normal control 6[366, 3800][366, 3800]Passed
normal control 7[366, 2900][366, 2900]Passed

SHA-256 / 0736ad86f97a65bfc8c85a84de3dae6922cf079dd75b2088d298435852e68b58

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
import calendar
N = 1
observations = []
def solve(x):
    s = datetime.date(*x['start'])
    try:
        e = s.replace(year=s.year + 1)
    except ValueError:
        e = datetime.date(s.year + 1, 3, 1)
    f = max(datetime.date(*x['from']), s + datetime.timedelta(days=1))
    t = min(datetime.date(*x['to']), e)
    days = max(0, (t - f).days)
    total = (e - s).days
    return [total, (x['price'] * days * 2 + total) // (2 * total)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 36500, 'start': [2020, 2, 29], 'from': [2020, 2, 18], 'to': [2020, 6, 27]}, [366, 11867]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('normal control', {'price': 119900, 'start': [2022, 1, 5], 'from': [2022, 2, 1], 'to': [2022, 5, 13]}, [365, 33178]), ('normal control', {'price': 617594, 'start': [2024, 4, 7], 'from': [2024, 5, 22], 'to': [2024, 7, 8]}, [365, 79526]), ('normal control', {'price': 36600, 'start': [2023, 6, 28], 'from': [2024, 5, 21], 'to': [2024, 9, 14]}, [366, 3800]), ('normal control', {'price': 36600, 'start': [2024, 1, 24], 'from': [2024, 4, 28], 'to': [2024, 5, 27]}, [366, 2900])], [('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('normal control', {'price': 119900, 'start': [2025, 7, 19], 'from': [2025, 8, 25], 'to': [2026, 1, 13]}, [365, 46318]), ('normal control', {'price': 975972, 'start': [2023, 4, 12], 'from': [2023, 10, 30], 'to': [2024, 1, 23]}, [366, 226660]), ('normal control', {'price': 401416, 'start': [2025, 2, 14], 'from': [2026, 1, 26], 'to': [2026, 2, 15]}, [365, 20896]), ('normal control', {'price': 36500, 'start': [2025, 4, 22], 'from': [2025, 10, 5], 'to': [2026, 2, 9]}, [365, 12700])], [('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('normal control', {'price': 505919, 'start': [2023, 11, 8], 'from': [2024, 5, 2], 'to': [2024, 8, 16]}, [366, 146523]), ('normal control', {'price': 36600, 'start': [2023, 7, 11], 'from': [2024, 5, 20], 'to': [2024, 7, 20]}, [366, 5200]), ('normal control', {'price': 698116, 'start': [2024, 2, 29], 'from': [2024, 7, 12], 'to': [2024, 7, 24]}, [366, 22889]), ('normal control', {'price': 100385, 'start': [2025, 10, 15], 'from': [2026, 10, 7], 'to': [2026, 10, 15]}, [365, 2200])], [('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('partial-repair probe', {'price': 119900, 'start': [2022, 7, 9], 'from': [2022, 6, 29], 'to': [2022, 12, 28]}, [365, 56501]), ('partial-repair probe', {'price': 314599, 'start': [2024, 9, 25], 'from': [2024, 9, 11], 'to': [2024, 11, 27]}, [365, 54301]), ('normal control', {'price': 36600, 'start': [2023, 4, 2], 'from': [2024, 2, 21], 'to': [2024, 5, 8]}, [366, 4100]), ('normal control', {'price': 466996, 'start': [2020, 2, 29], 'from': [2020, 8, 12], 'to': [2020, 11, 7]}, [366, 111007]), ('normal control', {'price': 119900, 'start': [2024, 6, 29], 'from': [2024, 9, 5], 'to': [2025, 3, 15]}, [365, 62742]), ('normal control', {'price': 36600, 'start': [2023, 8, 24], 'from': [2024, 4, 5], 'to': [2024, 5, 29]}, [366, 5400])], [('regression', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 697175, 'start': [2022, 12, 16], 'from': [2022, 12, 13], 'to': [2023, 3, 31]}, [365, 200557]), ('partial-repair probe', {'price': 119900, 'start': [2022, 4, 19], 'from': [2022, 4, 14], 'to': [2022, 5, 7]}, [365, 5913]), ('normal control', {'price': 36600, 'start': [2023, 5, 5], 'from': [2023, 7, 11], 'to': [2023, 7, 15]}, [366, 400]), ('normal control', {'price': 119900, 'start': [2023, 8, 26], 'from': [2023, 12, 8], 'to': [2023, 12, 16]}, [366, 2621]), ('normal control', {'price': 36500, 'start': [2024, 2, 29], 'from': [2025, 1, 6], 'to': [2025, 5, 17]}, [366, 5385]), ('normal control', {'price': 36500, 'start': [2022, 5, 14], 'from': [2022, 8, 4], 'to': [2022, 11, 25]}, [365, 11300])]]
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 fixtureActualExpectedOutcome
regression 0[366, 11768][366, 11867]Failed
regression 1[366, 0][366, 0]Passed
partial-repair probe 2[366, 2992][366, 3092]Failed
partial-repair probe 3[365, 1304][365, 1404]Failed
normal control 4[365, 33178][365, 33178]Passed
normal control 5[365, 79526][365, 79526]Passed
normal control 6[366, 3800][366, 3800]Passed
normal control 7[366, 2900][366, 2900]Passed

SHA-256 / cf0e7188cf8d7f9d40ebc8cae885450c106e66ff9d8900f0e745b91d24afb732

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
import calendar
N = 1
observations = []
def solve(x):
    s = datetime.date(*x['start'])
    try:
        e = s.replace(year=s.year + 1)
    except ValueError:
        e = datetime.date(s.year + 1, 3, 1)
    f = max(datetime.date(*x['from']), s)
    t = min(datetime.date(*x['to']), e)
    days = max(0, (t - f).days)
    total = (e - s).days
    return [total, (x['price'] * days * 2 + total) // (2 * total)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'price': 36500, 'start': [2020, 2, 29], 'from': [2020, 2, 18], 'to': [2020, 6, 27]}, [366, 11867]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('normal control', {'price': 119900, 'start': [2022, 1, 5], 'from': [2022, 2, 1], 'to': [2022, 5, 13]}, [365, 33178]), ('normal control', {'price': 617594, 'start': [2024, 4, 7], 'from': [2024, 5, 22], 'to': [2024, 7, 8]}, [365, 79526]), ('normal control', {'price': 36600, 'start': [2023, 6, 28], 'from': [2024, 5, 21], 'to': [2024, 9, 14]}, [366, 3800]), ('normal control', {'price': 36600, 'start': [2024, 1, 24], 'from': [2024, 4, 28], 'to': [2024, 5, 27]}, [366, 2900])], [('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('regression', {'price': 36600, 'start': [2023, 12, 24], 'from': [2023, 12, 9], 'to': [2023, 12, 10]}, [366, 0]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 16], 'from': [2022, 12, 16], 'to': [2022, 12, 30]}, [365, 1404]), ('partial-repair probe', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('normal control', {'price': 119900, 'start': [2025, 7, 19], 'from': [2025, 8, 25], 'to': [2026, 1, 13]}, [365, 46318]), ('normal control', {'price': 975972, 'start': [2023, 4, 12], 'from': [2023, 10, 30], 'to': [2024, 1, 23]}, [366, 226660]), ('normal control', {'price': 401416, 'start': [2025, 2, 14], 'from': [2026, 1, 26], 'to': [2026, 2, 15]}, [365, 20896]), ('normal control', {'price': 36500, 'start': [2025, 4, 22], 'from': [2025, 10, 5], 'to': [2026, 2, 9]}, [365, 12700])], [('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('regression', {'price': 36500, 'start': [2023, 5, 30], 'from': [2023, 5, 17], 'to': [2023, 6, 30]}, [366, 3092]), ('partial-repair probe', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('normal control', {'price': 505919, 'start': [2023, 11, 8], 'from': [2024, 5, 2], 'to': [2024, 8, 16]}, [366, 146523]), ('normal control', {'price': 36600, 'start': [2023, 7, 11], 'from': [2024, 5, 20], 'to': [2024, 7, 20]}, [366, 5200]), ('normal control', {'price': 698116, 'start': [2024, 2, 29], 'from': [2024, 7, 12], 'to': [2024, 7, 24]}, [366, 22889]), ('normal control', {'price': 100385, 'start': [2025, 10, 15], 'from': [2026, 10, 7], 'to': [2026, 10, 15]}, [365, 2200])], [('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('regression', {'price': 36600, 'start': [2022, 12, 27], 'from': [2022, 12, 11], 'to': [2023, 1, 25]}, [365, 2908]), ('partial-repair probe', {'price': 119900, 'start': [2022, 7, 9], 'from': [2022, 6, 29], 'to': [2022, 12, 28]}, [365, 56501]), ('partial-repair probe', {'price': 314599, 'start': [2024, 9, 25], 'from': [2024, 9, 11], 'to': [2024, 11, 27]}, [365, 54301]), ('normal control', {'price': 36600, 'start': [2023, 4, 2], 'from': [2024, 2, 21], 'to': [2024, 5, 8]}, [366, 4100]), ('normal control', {'price': 466996, 'start': [2020, 2, 29], 'from': [2020, 8, 12], 'to': [2020, 11, 7]}, [366, 111007]), ('normal control', {'price': 119900, 'start': [2024, 6, 29], 'from': [2024, 9, 5], 'to': [2025, 3, 15]}, [365, 62742]), ('normal control', {'price': 36600, 'start': [2023, 8, 24], 'from': [2024, 4, 5], 'to': [2024, 5, 29]}, [366, 5400])], [('regression', {'price': 36600, 'start': [2022, 5, 13], 'from': [2022, 5, 8], 'to': [2022, 6, 19]}, [365, 3710]), ('regression', {'price': 306491, 'start': [2025, 9, 26], 'from': [2025, 9, 7], 'to': [2026, 3, 21]}, [365, 147787]), ('partial-repair probe', {'price': 697175, 'start': [2022, 12, 16], 'from': [2022, 12, 13], 'to': [2023, 3, 31]}, [365, 200557]), ('partial-repair probe', {'price': 119900, 'start': [2022, 4, 19], 'from': [2022, 4, 14], 'to': [2022, 5, 7]}, [365, 5913]), ('normal control', {'price': 36600, 'start': [2023, 5, 5], 'from': [2023, 7, 11], 'to': [2023, 7, 15]}, [366, 400]), ('normal control', {'price': 119900, 'start': [2023, 8, 26], 'from': [2023, 12, 8], 'to': [2023, 12, 16]}, [366, 2621]), ('normal control', {'price': 36500, 'start': [2024, 2, 29], 'from': [2025, 1, 6], 'to': [2025, 5, 17]}, [366, 5385]), ('normal control', {'price': 36500, 'start': [2022, 5, 14], 'from': [2022, 8, 4], 'to': [2022, 11, 25]}, [365, 11300])]]
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 fixtureActualExpectedOutcome
regression 0[366, 11867][366, 11867]Passed
regression 1[366, 0][366, 0]Passed
partial-repair probe 2[366, 3092][366, 3092]Passed
partial-repair probe 3[365, 1404][365, 1404]Passed
normal control 4[365, 33178][365, 33178]Passed
normal control 5[365, 79526][365, 79526]Passed
normal control 6[366, 3800][366, 3800]Passed
normal control 7[366, 2900][366, 2900]Passed

SHA-256 / 1ff417c3f75f18c1623291fdfb6d0a9920ad08413e6c43488486910479c91f7b

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 2026-09-29T14:46:38.175222+00:00.

Case digest / 9bc6b56e74ee4e5695b806d80b91e1c65c8a3523ef4e1e084892cd9e1ad73ab1