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FA-58531 / Loan amortization schedules / Open access

Late fee after grace period: unpaid lateness end · case 01

Late payments report lateness up to the statement date instead of the payment date.

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

ROOT CAUSE

The as-of day is used even when a payment was received.

VERIFIED REPAIR

Use the payment day when paid and as_of only when unpaid.

Unsuccessful approach: Using the grace deadline for unpaid loans understates delinquency.

Case contract

x = {'due_day', 'grace', 'paid_day' or None, 'payment_due', 'paid_amount', 'tolerance', 'fee_bp', 'fee_min', 'fee_max', 'as_of'}. A payment is on time when paid_day is not None, paid_day <= due_day + grace and payment_due - paid_amount <= tolerance. Otherwise fee = clamp(round_half_up(payment_due*fee_bp/10000), fee_min, fee_max) and days_late = max(0, (paid_day or as_of when unpaid) - due_day). Return {'late', 'fee', 'days_late'}.

Why this case matters

Amortization engines drive borrower statements, payoff quotes and investor remittances; a misplaced rounding step, boundary or ordering rule compounds across hundreds of periods.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def rnd(n, d):
        q, r = divmod(n, d)
        return q + (1 if 2 * r >= d else 0)
    deadline = x['due_day'] + x['grace']
    paid = x['paid_day']
    short = x['payment_due'] - x['paid_amount']
    on_time = paid is not None and paid <= deadline and short <= x['tolerance']
    if on_time:
        return {'late': False, 'fee': 0, 'days_late': 0}
    end = x['as_of']
    fee = rnd(x['payment_due'] * x['fee_bp'], 10000)
    fee = max(x['fee_min'], min(fee, x['fee_max']))
    return {'late': True, 'fee': fee, 'days_late': max(0, end - x['due_day'])}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: unpaid lateness end', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 15, 'paid_day': 20, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 5', {'due_day': 1, 'grace': 0, 'paid_day': 0, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 2500, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 15, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 55}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 1', {'due_day': 15, 'grace': 15, 'paid_day': 18, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 15, 'paid_day': 8, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 10, 'paid_day': 5, 'payment_due': 100000, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 4000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 0, 'paid_day': 14, 'payment_due': 100000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 2500, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 1, 'grace': 15, 'paid_day': 0, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 0, 'paid_day': 6, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 100, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 15, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 20}], ['control 1', {'due_day': 1, 'grace': 10, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 150000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': True, 'fee': 4000, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 10, 'paid_day': 14, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 4', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 0, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 1500, 'days_late': 20}]]]
for label, args, expected in fixtures[N-1]:
    try:
        actual = solve(args)
    except Exception as exc:
        actual = 'raised ' + type(exc).__name__
    check(label, actual, 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: unpaid lateness end{'days_late': 20, 'fee': 5000, 'late': True}{'days_late': 0, 'fee': 5000, 'late': True}Failed
regression: unpaid lateness end, partial-repair probe{'days_late': 40, 'fee': 5000, 'late': True}{'days_late': 40, 'fee': 5000, 'late': True}Passed
control 1{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 2{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 3{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 4{'days_late': 40, 'fee': 2500, 'late': True}{'days_late': 40, 'fee': 2500, 'late': True}Passed
control 5{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed

SHA-256 / 6f8d6229b0d53f2b28c5b25f8161086f2d94796919b6ff9d06019f7b10836c1d

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def rnd(n, d):
        q, r = divmod(n, d)
        return q + (1 if 2 * r >= d else 0)
    deadline = x['due_day'] + x['grace']
    paid = x['paid_day']
    short = x['payment_due'] - x['paid_amount']
    on_time = paid is not None and paid <= deadline and short <= x['tolerance']
    if on_time:
        return {'late': False, 'fee': 0, 'days_late': 0}
    end = paid if paid is not None else deadline
    fee = rnd(x['payment_due'] * x['fee_bp'], 10000)
    fee = max(x['fee_min'], min(fee, x['fee_max']))
    return {'late': True, 'fee': fee, 'days_late': max(0, end - x['due_day'])}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: unpaid lateness end', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 15, 'paid_day': 20, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 5', {'due_day': 1, 'grace': 0, 'paid_day': 0, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 2500, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 15, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 55}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 1', {'due_day': 15, 'grace': 15, 'paid_day': 18, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 15, 'paid_day': 8, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 10, 'paid_day': 5, 'payment_due': 100000, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 4000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 0, 'paid_day': 14, 'payment_due': 100000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 2500, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 1, 'grace': 15, 'paid_day': 0, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 0, 'paid_day': 6, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 100, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 15, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 20}], ['control 1', {'due_day': 1, 'grace': 10, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 150000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': True, 'fee': 4000, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 10, 'paid_day': 14, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 4', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 0, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 1500, 'days_late': 20}]]]
for label, args, expected in fixtures[N-1]:
    try:
        actual = solve(args)
    except Exception as exc:
        actual = 'raised ' + type(exc).__name__
    check(label, actual, 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: unpaid lateness end{'days_late': 0, 'fee': 5000, 'late': True}{'days_late': 0, 'fee': 5000, 'late': True}Passed
regression: unpaid lateness end, partial-repair probe{'days_late': 15, 'fee': 5000, 'late': True}{'days_late': 40, 'fee': 5000, 'late': True}Failed
control 1{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 2{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 3{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 4{'days_late': 0, 'fee': 2500, 'late': True}{'days_late': 40, 'fee': 2500, 'late': True}Failed
control 5{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed

SHA-256 / 00db3166230233a76dca67510e42735fe472bbbc1fc5ce95139da89d0ce9ee26

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def rnd(n, d):
        q, r = divmod(n, d)
        return q + (1 if 2 * r >= d else 0)
    deadline = x['due_day'] + x['grace']
    paid = x['paid_day']
    short = x['payment_due'] - x['paid_amount']
    on_time = paid is not None and paid <= deadline and short <= x['tolerance']
    if on_time:
        return {'late': False, 'fee': 0, 'days_late': 0}
    end = paid if paid is not None else x['as_of']
    fee = rnd(x['payment_due'] * x['fee_bp'], 10000)
    fee = max(x['fee_min'], min(fee, x['fee_max']))
    return {'late': True, 'fee': fee, 'days_late': max(0, end - x['due_day'])}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: unpaid lateness end', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 150000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 15, 'paid_day': 20, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 5', {'due_day': 1, 'grace': 0, 'paid_day': 0, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 2500, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 15, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 55}, {'late': True, 'fee': 2500, 'days_late': 40}], ['control 1', {'due_day': 15, 'grace': 15, 'paid_day': 18, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 5, 'grace': 15, 'paid_day': 8, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 0, 'paid_day': 4, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 10, 'paid_day': 5, 'payment_due': 100000, 'paid_amount': 99999, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 4000, 'days_late': 0}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 0, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 1', {'due_day': 5, 'grace': 0, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 0, 'paid_day': 14, 'payment_due': 100000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 2500, 'paid_amount': 150000, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 2500, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 1, 'grace': 15, 'paid_day': 0, 'payment_due': 2500, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 5, 'grace': 0, 'paid_day': 6, 'payment_due': 2500, 'paid_amount': 0, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 45}, {'late': True, 'fee': 100, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 15, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 150000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 25}, {'late': True, 'fee': 5000, 'days_late': 20}], ['control 1', {'due_day': 1, 'grace': 10, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 20000, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 20000, 'paid_amount': 99999, 'tolerance': 10, 'fee_bp': 400, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 4', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 150000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 10000, 'as_of': 21}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 15, 'paid_day': 5, 'payment_due': 2500, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': False, 'fee': 0, 'days_late': 0}]], [['regression: unpaid lateness end', {'due_day': 1, 'grace': 0, 'paid_day': 2, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 100, 'fee_bp': 400, 'fee_min': 0, 'fee_max': 5000, 'as_of': 21}, {'late': True, 'fee': 4000, 'days_late': 1}], ['regression: unpaid lateness end, partial-repair probe', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 2500, 'fee_max': 10000, 'as_of': 45}, {'late': True, 'fee': 5000, 'days_late': 40}], ['control 1', {'due_day': 1, 'grace': 0, 'paid_day': 1, 'payment_due': 100000, 'paid_amount': 149990, 'tolerance': 0, 'fee_bp': 400, 'fee_min': 2500, 'fee_max': 5000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 2', {'due_day': 15, 'grace': 10, 'paid_day': 14, 'payment_due': 150000, 'paid_amount': 150000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 0, 'fee_max': 5000, 'as_of': 35}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 3', {'due_day': 1, 'grace': 15, 'paid_day': None, 'payment_due': 2500, 'paid_amount': 20000, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 5000, 'as_of': 41}, {'late': True, 'fee': 1500, 'days_late': 40}], ['control 4', {'due_day': 1, 'grace': 15, 'paid_day': 16, 'payment_due': 20000, 'paid_amount': 100000, 'tolerance': 10, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 41}, {'late': False, 'fee': 0, 'days_late': 0}], ['control 5', {'due_day': 5, 'grace': 10, 'paid_day': None, 'payment_due': 20000, 'paid_amount': 0, 'tolerance': 100, 'fee_bp': 500, 'fee_min': 1500, 'fee_max': 10000, 'as_of': 25}, {'late': True, 'fee': 1500, 'days_late': 20}]]]
for label, args, expected in fixtures[N-1]:
    try:
        actual = solve(args)
    except Exception as exc:
        actual = 'raised ' + type(exc).__name__
    check(label, actual, 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: unpaid lateness end{'days_late': 0, 'fee': 5000, 'late': True}{'days_late': 0, 'fee': 5000, 'late': True}Passed
regression: unpaid lateness end, partial-repair probe{'days_late': 40, 'fee': 5000, 'late': True}{'days_late': 40, 'fee': 5000, 'late': True}Passed
control 1{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 2{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 3{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed
control 4{'days_late': 40, 'fee': 2500, 'late': True}{'days_late': 40, 'fee': 2500, 'late': True}Passed
control 5{'days_late': 0, 'fee': 0, 'late': False}{'days_late': 0, 'fee': 0, 'late': False}Passed

SHA-256 / 7d2bf22649126d8ee021350ebe552614276566093c318b4ce8265268b3272196

Verification & scope

A deterministic bounded teaching model with stipulated toy lending rules stated in the contract; money is integer cents and rates are basis points; it makes no claim of conformance to any regulation, servicing standard or product. 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 2026-09-29T14:46:27.551744+00:00.

Case digest / 604b498bba1bde580a5becc8303fdbb0bbca1c922813827099423b08a278fdeb