FA-60701 / Loyalty points ledgers / Open access

Birthday bonus window: neighbouring birthday years · case 01

Purchases in late December miss an early-January birthday window.

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

ROOT CAUSE

Only the birthday in the purchase calendar year is checked.

VERIFIED REPAIR

Check the birthdays of the previous, current and next year.

Unsuccessful approach: Checking the current and next year still misses early-January purchases for a late-December birthday.

Case contract

Input {bmonth, bday, window, bonus, purchases:[[y,m,d]] chronological}. The birthday of year Y is (Y,bmonth,bday), with Feb 29 falling back to Feb 28 in non-leap years (Gregorian rule). A purchase within window days (inclusive, either side) of the birthday of year Y-1, Y or Y+1 earns the bonus once per birthday year. Return per-purchase bonus list.

Why this case matters

Member point balances, statements and the program liability depend on this ledger rule.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
N = 1
observations = []
def solve(x):
    def bday(y):
        m, d = x['bmonth'], x['bday']
        if m == 2 and d == 29 and not (y % 4 == 0 and (y % 100 != 0 or y % 400 == 0)):
            d = 28
        return datetime.date(y, m, d)
    got = set()
    out = []
    for y, m, d in x['purchases']:
        p = datetime.date(y, m, d)
        award = 0
        for yy in (y,):
            if abs((p - bday(yy)).days) <= x['window'] and yy not in got:
                got.add(yy)
                award = x['bonus']
                break
        out.append(award)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 11], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 8]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 801, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [801, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 21], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 12], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 9]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 802, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [802, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 22], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 13], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 10]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 28], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 803, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [803, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 23], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 14], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 11]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 804, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [804, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 24], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 15], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 12]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 805, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [805, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 25], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
inside window	`[500, 0]`	`[500, 0]`	Passed
window edge	`[500, 0]`	`[500, 0]`	Passed
year crossing	`[0, 300]`	`[300, 0]`	Failed
late december birthday	`[0, 250]`	`[250, 250]`	Failed
leap day	`[800, 800, 0]`	`[800, 800, 0]`	Passed
century year	`[801, 0]`	`[801, 0]`	Passed
before birthday only	`[0, 100, 0]`	`[0, 100, 0]`	Passed

SHA-256 / 4d519a74f0f8ad92b0635d04ba2979ab456998dcd338a60f1fcf174786d294b8

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
N = 1
observations = []
def solve(x):
    def bday(y):
        m, d = x['bmonth'], x['bday']
        if m == 2 and d == 29 and not (y % 4 == 0 and (y % 100 != 0 or y % 400 == 0)):
            d = 28
        return datetime.date(y, m, d)
    got = set()
    out = []
    for y, m, d in x['purchases']:
        p = datetime.date(y, m, d)
        award = 0
        for yy in (y, y + 1):
            if abs((p - bday(yy)).days) <= x['window'] and yy not in got:
                got.add(yy)
                award = x['bonus']
                break
        out.append(award)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 11], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 8]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 801, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [801, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 21], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 12], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 9]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 802, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [802, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 22], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 13], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 10]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 28], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 803, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [803, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 23], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 14], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 11]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 804, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [804, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 24], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 15], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 12]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 805, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [805, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 25], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
inside window	`[500, 0]`	`[500, 0]`	Passed
window edge	`[500, 0]`	`[500, 0]`	Passed
year crossing	`[300, 0]`	`[300, 0]`	Passed
late december birthday	`[0, 250]`	`[250, 250]`	Failed
leap day	`[800, 800, 0]`	`[800, 800, 0]`	Passed
century year	`[801, 0]`	`[801, 0]`	Passed
before birthday only	`[0, 100, 0]`	`[0, 100, 0]`	Passed

SHA-256 / 363797eb03b74a117f1b9ff1e5cf3db657553b70283f35c17b620df069a013c0

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
N = 1
observations = []
def solve(x):
    def bday(y):
        m, d = x['bmonth'], x['bday']
        if m == 2 and d == 29 and not (y % 4 == 0 and (y % 100 != 0 or y % 400 == 0)):
            d = 28
        return datetime.date(y, m, d)
    got = set()
    out = []
    for y, m, d in x['purchases']:
        p = datetime.date(y, m, d)
        award = 0
        for yy in (y - 1, y, y + 1):
            if abs((p - bday(yy)).days) <= x['window'] and yy not in got:
                got.add(yy)
                award = x['bonus']
                break
        out.append(award)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 11], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 8]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 801, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [801, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 21], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 12], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 9]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 802, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [802, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 22], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 13], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 10]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 28], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 803, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [803, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 23], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 14], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 11]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 29], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 2], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 804, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [804, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 24], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]], [['inside window', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2024, 6, 15], [2024, 6, 20]]}, [500, 0]], ['window edge', {'bmonth': 6, 'bday': 15, 'window': 7, 'bonus': 500, 'purchases': [[2023, 6, 22], [2023, 6, 12]]}, [500, 0]], ['year crossing', {'bmonth': 1, 'bday': 3, 'window': 7, 'bonus': 300, 'purchases': [[2023, 12, 30], [2024, 1, 5]]}, [300, 0]], ['late december birthday', {'bmonth': 12, 'bday': 30, 'window': 5, 'bonus': 250, 'purchases': [[2025, 1, 3], [2025, 12, 29]]}, [250, 250]], ['leap day', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 800, 'purchases': [[2023, 2, 28], [2024, 2, 29], [2023, 3, 1]]}, [800, 800, 0]], ['century year', {'bmonth': 2, 'bday': 29, 'window': 0, 'bonus': 805, 'purchases': [[2100, 2, 28], [2100, 3, 1]]}, [805, 0]], ['before birthday only', {'bmonth': 9, 'bday': 1, 'window': 3, 'bonus': 100, 'purchases': [[2024, 8, 25], [2024, 8, 30], [2024, 9, 3]]}, [0, 100, 0]]]]
for label, args, expected in fixtures[N-1]:
    check(label, 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
inside window	`[500, 0]`	`[500, 0]`	Passed
window edge	`[500, 0]`	`[500, 0]`	Passed
year crossing	`[300, 0]`	`[300, 0]`	Passed
late december birthday	`[250, 250]`	`[250, 250]`	Passed
leap day	`[800, 800, 0]`	`[800, 800, 0]`	Passed
century year	`[801, 0]`	`[801, 0]`	Passed
before birthday only	`[0, 100, 0]`	`[0, 100, 0]`	Passed

SHA-256 / c842cb4d7438dad16e02581497d87b36082a2eb5bd805aa8a6cdaa102ec8be39

Verification & scope

Stipulated bounded loyalty-program model with explicit toy rules; not any real program terms. 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 2026-09-29T14:46:48.013362+00:00.

Case digest / f61a45bba48f402a1f03f454f9505a17eaa4e4844cc079c05d97ac8310b8ce3b