FA-76901 / Calendar recurrence rules / Open access
Monthly ordinal BYDAY such as 2TU or -1FR: negative ordinal base · case 01
BYDAY=-1FR lands a week before the last Friday.
ROOT CAUSE
Negative ordinals step back ordinal weeks instead of ordinal-1 weeks from the last matching weekday.
VERIFIED REPAIR
At the negative ordinal base decision use `7 * (ordinal + 1)`, leaving the other decision sites of the model unchanged.
Unsuccessful approach: The partial repair `7 * (abs(ordinal) - 1)` uses the magnitude, so -2 steps forward past the last occurrence.
Case contract
FREQ=MONTHLY;BYDAY=<ordinal><weekday>. weekday is 0=Monday..6=Sunday; ordinal 1..5 counts from the start of the month and -1..-5 from the end. A month lacking that occurrence is skipped and does not consume COUNT. Months step by interval from the dtstart month; instances before dtstart are dropped. Return the first count ISO dates.
Why this case matters
Recurring calendar series are expanded into concrete instances for display, reminders and conflict checks.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import datetime as dt
import calendar
N = 1
observations = []
def solve(dtstart, interval, ordinal, weekday, count):
start = dt.date.fromisoformat(dtstart)
out = []
for k in range(600):
if len(out) >= count:
return out
mi = start.month - 1 + k * interval
y, m = start.year + mi // 12, mi % 12 + 1
dim = calendar.monthrange(y, m)[1]
first_wd = dt.date(y, m, 1).weekday()
last_wd = dt.date(y, m, dim).weekday()
if ordinal > 0:
day = 1 + (weekday - first_wd) % 7 + 7 * (ordinal - 1)
else:
day = dim - (last_wd - weekday) % 7 + 7 * ordinal
if day < 1 or day > dim:
continue
d = dt.date(y, m, day)
if d < start:
continue
out.append(d.isoformat())
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05'])],
[('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25'])],
[('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], [])],
[('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01'])],
[('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'])]]
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 |
|---|---|---|---|
| regression: second tuesday | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | Passed |
| last friday | ['2024-01-19', '2024-02-16', '2024-03-22', '2024-04-19'] | ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26'] | Failed |
| second to last sunday | ['2024-02-11', '2024-03-17', '2024-04-14', '2024-05-12'] | ['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'] | Failed |
| fifth monday skips months | ['2024-01-29', '2024-04-29', '2024-07-29'] | ['2024-01-29', '2024-04-29', '2024-07-29'] | Passed |
| fifth-to-last thursday | [] | ['2024-02-01', '2024-05-02', '2024-08-01'] | Failed |
| interval 2 first saturday | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | Passed |
| first-month occurrence before dtstart | ['2024-04-03', '2024-05-01', '2024-06-05'] | ['2024-04-03', '2024-05-01', '2024-06-05'] | Passed |
SHA-256 / bfd0d3aee78a9b42994f0713ca06fd02faa7a3fa84e252fc9fe16227e189c520
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
import datetime as dt
import calendar
N = 1
observations = []
def solve(dtstart, interval, ordinal, weekday, count):
start = dt.date.fromisoformat(dtstart)
out = []
for k in range(600):
if len(out) >= count:
return out
mi = start.month - 1 + k * interval
y, m = start.year + mi // 12, mi % 12 + 1
dim = calendar.monthrange(y, m)[1]
first_wd = dt.date(y, m, 1).weekday()
last_wd = dt.date(y, m, dim).weekday()
if ordinal > 0:
day = 1 + (weekday - first_wd) % 7 + 7 * (ordinal - 1)
else:
day = dim - (last_wd - weekday) % 7 + 7 * (abs(ordinal) - 1)
if day < 1 or day > dim:
continue
d = dt.date(y, m, day)
if d < start:
continue
out.append(d.isoformat())
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05'])],
[('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25'])],
[('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], [])],
[('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01'])],
[('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'])]]
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 |
|---|---|---|---|
| regression: second tuesday | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | Passed |
| last friday | ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26'] | ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26'] | Passed |
| second to last sunday | [] | ['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'] | Failed |
| fifth monday skips months | ['2024-01-29', '2024-04-29', '2024-07-29'] | ['2024-01-29', '2024-04-29', '2024-07-29'] | Passed |
| fifth-to-last thursday | [] | ['2024-02-01', '2024-05-02', '2024-08-01'] | Failed |
| interval 2 first saturday | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | Passed |
| first-month occurrence before dtstart | ['2024-04-03', '2024-05-01', '2024-06-05'] | ['2024-04-03', '2024-05-01', '2024-06-05'] | Passed |
SHA-256 / 4524c7361162327fbb7866e573f651b2abca711cb41d508bd9c96e51dc2082d6
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
import datetime as dt
import calendar
N = 1
observations = []
def solve(dtstart, interval, ordinal, weekday, count):
start = dt.date.fromisoformat(dtstart)
out = []
for k in range(600):
if len(out) >= count:
return out
mi = start.month - 1 + k * interval
y, m = start.year + mi // 12, mi % 12 + 1
dim = calendar.monthrange(y, m)[1]
first_wd = dt.date(y, m, 1).weekday()
last_wd = dt.date(y, m, dim).weekday()
if ordinal > 0:
day = 1 + (weekday - first_wd) % 7 + 7 * (ordinal - 1)
else:
day = dim - (last_wd - weekday) % 7 + 7 * (ordinal + 1)
if day < 1 or day > dim:
continue
d = dt.date(y, m, day)
if d < start:
continue
out.append(d.isoformat())
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05'])],
[('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19']),
('fifth monday skips months', ['2024-01-01', 1, 5, 0, 3], ['2024-01-29', '2024-04-29', '2024-07-29']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25'])],
[('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01']),
('interval 2 first saturday',
['2024-11-01', 2, 1, 5, 4],
['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03']),
('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], [])],
[('first-month occurrence before dtstart',
['2024-03-20', 1, 1, 2, 3],
['2024-04-03', '2024-05-01', '2024-06-05']),
('third wednesday quarterly',
['2023-12-01', 3, 3, 2, 4],
['2023-12-20', '2024-03-20', '2024-06-19', '2024-09-18']),
('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('fifth-to-last thursday', ['2024-01-01', 1, -5, 3, 3], ['2024-02-01', '2024-05-02', '2024-08-01'])],
[('fourth sunday', ['2025-02-10', 1, 4, 6, 4], ['2025-02-23', '2025-03-23', '2025-04-27', '2025-05-25']),
('last monday dtstart on it', ['2024-05-27', 1, -1, 0, 3], ['2024-05-27', '2024-06-24', '2024-07-29']),
('count zero', ['2024-01-01', 1, 1, 0, 0], []),
('fifth friday interval 1',
['2024-02-01', 1, 5, 4, 4],
['2024-03-29', '2024-05-31', '2024-08-30', '2024-11-29']),
('regression: second tuesday',
['2024-01-01', 1, 2, 1, 4],
['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09']),
('last friday', ['2024-01-01', 1, -1, 4, 4], ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26']),
('second to last sunday',
['2024-02-01', 1, -2, 6, 4],
['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'])]]
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 |
|---|---|---|---|
| regression: second tuesday | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | ['2024-01-09', '2024-02-13', '2024-03-12', '2024-04-09'] | Passed |
| last friday | ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26'] | ['2024-01-26', '2024-02-23', '2024-03-29', '2024-04-26'] | Passed |
| second to last sunday | ['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'] | ['2024-02-18', '2024-03-24', '2024-04-21', '2024-05-19'] | Passed |
| fifth monday skips months | ['2024-01-29', '2024-04-29', '2024-07-29'] | ['2024-01-29', '2024-04-29', '2024-07-29'] | Passed |
| fifth-to-last thursday | ['2024-02-01', '2024-05-02', '2024-08-01'] | ['2024-02-01', '2024-05-02', '2024-08-01'] | Passed |
| interval 2 first saturday | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | ['2024-11-02', '2025-01-04', '2025-03-01', '2025-05-03'] | Passed |
| first-month occurrence before dtstart | ['2024-04-03', '2024-05-01', '2024-06-05'] | ['2024-04-03', '2024-05-01', '2024-06-05'] | Passed |
SHA-256 / dc6344d5aafc004f6915d5f2fd02d052e89703de051878190a01183c46bca7c1
Verification & scope
Stipulated, bounded recurrence-expansion model evaluated offline on explicit fixtures; it is not a complete iCalendar implementation and makes no claim of standards conformance. 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 2026-09-29T14:49:20.576578+00:00.
Case digest / c8978d72333aed199e6880959b86688d84f0340f41f7f66a576e2decce656800