FA-59396 / Subscription proration billing / Open access

Month-end anchored renewal dates: zero-based month index · case 01

Every renewal is scheduled one month late.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The anchor month is not converted to a zero-based index before adding intervals.

VERIFIED REPAIR

Restore the contract rule at the zero-based month index step: use `total = (m - 1) + i * x['interval']`.

Unsuccessful approach: The attempt fixes the index but counts from renewal zero, repeating the anchor date as the first renewal.

Case contract

Input {anchor [y,m,d], n, interval months}. Renewal i (1..n) falls interval*i months after the anchor month, on the anchor day clamped to that month's length (so a 31st anchor returns to the 31st whenever possible). Return the list of [y, m, d].

Why this case matters

Month-end anchors must not drift to the 28th after February, and leap years change the clamp.

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):
    y, m, d = x['anchor']
    out = []
    for i in range(1, x['n'] + 1):
        total = m + i * x['interval']
        ny, nm = y + total // 12, total % 12 + 1
        dim = calendar.monthrange(ny, nm)[1]
        out.append([ny, nm, min(d, dim)])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'anchor': [2024, 7, 30], 'n': 7, 'interval': 3}, [[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]), ('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('partial-repair probe', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('additional oracle', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]])], [('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]])], [('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]])], [('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('partial-repair probe', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('additional oracle', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]])], [('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('regression', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('partial-repair probe', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 3, 31], 'n': 7, 'interval': 12}, [[2026, 3, 31], [2027, 3, 31], [2028, 3, 31], [2029, 3, 31], [2030, 3, 31], [2031, 3, 31], [2032, 3, 31]])]]
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	`[[2024, 11, 30], [2025, 2, 28], [2025, 5, 30], [2025, 8, 30], [2025, 11, 30], [2026, 2, 28], [2026, 5, 30]]`	`[[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]`	Failed
regression 1	`[[2025, 8, 31], [2025, 10, 31], [2025, 12, 31], [2026, 2, 28], [2026, 4, 30], [2026, 6, 30], [2026, 8, 31], [2026, 10, 31], [2026, 12, 31], [2027, 2, 28]]`	`[[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]`	Failed
partial-repair probe 2	`[[2019, 8, 29], [2019, 10, 29], [2019, 12, 29], [2020, 2, 29], [2020, 4, 29], [2020, 6, 29], [2020, 8, 29], [2020, 10, 29], [2020, 12, 29], [2021, 2, 28], [2021, 4, 29]]`	`[[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]`	Failed
partial-repair probe 3	`[[2023, 7, 28], [2023, 10, 28], [2024, 1, 28], [2024, 4, 28], [2024, 7, 28], [2024, 10, 28], [2025, 1, 28], [2025, 4, 28], [2025, 7, 28], [2025, 10, 28], [2026, 1, 28], [2026, 4, 28], [2026, 7, 28], [2026, 10, 28]]`	`[[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]`	Failed
additional oracle 4	`[[2024, 5, 29], [2024, 7, 29], [2024, 9, 29], [2024, 11, 29], [2025, 1, 29], [2025, 3, 29]]`	`[[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]`	Failed
additional oracle 5	`[[2025, 10, 28]]`	`[[2025, 9, 28]]`	Failed
additional oracle 6	`[[2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31], [2024, 8, 31]]`	`[[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]`	Failed

SHA-256 / 3085b69f00089e8e71b8952313e705181077b707fdebd547b5ef9e835ad60ced

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):
    y, m, d = x['anchor']
    out = []
    for i in range(1, x['n'] + 1):
        total = (m - 1) + (i - 1) * x['interval']
        ny, nm = y + total // 12, total % 12 + 1
        dim = calendar.monthrange(ny, nm)[1]
        out.append([ny, nm, min(d, dim)])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'anchor': [2024, 7, 30], 'n': 7, 'interval': 3}, [[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]), ('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('partial-repair probe', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('additional oracle', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]])], [('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]])], [('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]])], [('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('partial-repair probe', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('additional oracle', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]])], [('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('regression', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('partial-repair probe', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 3, 31], 'n': 7, 'interval': 12}, [[2026, 3, 31], [2027, 3, 31], [2028, 3, 31], [2029, 3, 31], [2030, 3, 31], [2031, 3, 31], [2032, 3, 31]])]]
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	`[[2024, 7, 30], [2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30]]`	`[[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]`	Failed
regression 1	`[[2025, 5, 31], [2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30]]`	`[[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]`	Failed
partial-repair probe 2	`[[2019, 5, 29], [2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29]]`	`[[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]`	Failed
partial-repair probe 3	`[[2023, 3, 28], [2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28]]`	`[[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]`	Failed
additional oracle 4	`[[2024, 2, 29], [2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29]]`	`[[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]`	Failed
additional oracle 5	`[[2025, 8, 28]]`	`[[2025, 9, 28]]`	Failed
additional oracle 6	`[[2023, 12, 31], [2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30]]`	`[[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]`	Failed

SHA-256 / 131ab85e1b53b23e5beb7d1f4ca74a43c2c0134060c8bd9080529a10860ad288

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):
    y, m, d = x['anchor']
    out = []
    for i in range(1, x['n'] + 1):
        total = (m - 1) + i * x['interval']
        ny, nm = y + total // 12, total % 12 + 1
        dim = calendar.monthrange(ny, nm)[1]
        out.append([ny, nm, min(d, dim)])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'anchor': [2024, 7, 30], 'n': 7, 'interval': 3}, [[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]), ('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('partial-repair probe', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('additional oracle', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]])], [('regression', {'anchor': [2025, 5, 31], 'n': 10, 'interval': 2}, [[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]), ('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('partial-repair probe', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]])], [('regression', {'anchor': [2019, 5, 29], 'n': 11, 'interval': 2}, [[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]), ('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]])], [('regression', {'anchor': [2023, 3, 28], 'n': 14, 'interval': 3}, [[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]), ('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('partial-repair probe', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('partial-repair probe', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('additional oracle', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('additional oracle', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]])], [('regression', {'anchor': [2024, 2, 29], 'n': 6, 'interval': 2}, [[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]), ('regression', {'anchor': [2025, 8, 28], 'n': 1, 'interval': 1}, [[2025, 9, 28]]), ('partial-repair probe', {'anchor': [2024, 12, 29], 'n': 10, 'interval': 1}, [[2025, 1, 29], [2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29], [2025, 10, 29]]), ('partial-repair probe', {'anchor': [2025, 4, 28], 'n': 8, 'interval': 12}, [[2026, 4, 28], [2027, 4, 28], [2028, 4, 28], [2029, 4, 28], [2030, 4, 28], [2031, 4, 28], [2032, 4, 28], [2033, 4, 28]]), ('additional oracle', {'anchor': [2023, 12, 31], 'n': 7, 'interval': 1}, [[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]), ('additional oracle', {'anchor': [2025, 1, 29], 'n': 8, 'interval': 1}, [[2025, 2, 28], [2025, 3, 29], [2025, 4, 29], [2025, 5, 29], [2025, 6, 29], [2025, 7, 29], [2025, 8, 29], [2025, 9, 29]]), ('additional oracle', {'anchor': [2025, 3, 31], 'n': 7, 'interval': 12}, [[2026, 3, 31], [2027, 3, 31], [2028, 3, 31], [2029, 3, 31], [2030, 3, 31], [2031, 3, 31], [2032, 3, 31]])]]
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	`[[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]`	`[[2024, 10, 30], [2025, 1, 30], [2025, 4, 30], [2025, 7, 30], [2025, 10, 30], [2026, 1, 30], [2026, 4, 30]]`	Passed
regression 1	`[[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]`	`[[2025, 7, 31], [2025, 9, 30], [2025, 11, 30], [2026, 1, 31], [2026, 3, 31], [2026, 5, 31], [2026, 7, 31], [2026, 9, 30], [2026, 11, 30], [2027, 1, 31]]`	Passed
partial-repair probe 2	`[[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]`	`[[2019, 7, 29], [2019, 9, 29], [2019, 11, 29], [2020, 1, 29], [2020, 3, 29], [2020, 5, 29], [2020, 7, 29], [2020, 9, 29], [2020, 11, 29], [2021, 1, 29], [2021, 3, 29]]`	Passed
partial-repair probe 3	`[[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]`	`[[2023, 6, 28], [2023, 9, 28], [2023, 12, 28], [2024, 3, 28], [2024, 6, 28], [2024, 9, 28], [2024, 12, 28], [2025, 3, 28], [2025, 6, 28], [2025, 9, 28], [2025, 12, 28], [2026, 3, 28], [2026, 6, 28], [2026, 9, 28]]`	Passed
additional oracle 4	`[[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]`	`[[2024, 4, 29], [2024, 6, 29], [2024, 8, 29], [2024, 10, 29], [2024, 12, 29], [2025, 2, 28]]`	Passed
additional oracle 5	`[[2025, 9, 28]]`	`[[2025, 9, 28]]`	Passed
additional oracle 6	`[[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]`	`[[2024, 1, 31], [2024, 2, 29], [2024, 3, 31], [2024, 4, 30], [2024, 5, 31], [2024, 6, 30], [2024, 7, 31]]`	Passed

SHA-256 / c4dcf9b9ff945148404e1b2f2ff23f237383844917f6e21eeb9c83e74c345324

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 2026-09-29T14:46:35.864427+00:00.

Case digest / 76a0fc6fbc0ea8e1f432642e87238ec0bdcb40ae30ad145cb0cf1485b14d3880