FA-59431 / Subscription proration billing / Open access
Trial conversion stub period: previous anchor January wrap · case 01
January trials that end before the anchor day produce a negative stub charge.
ROOT CAUSE
The previous anchor for a January trial end is placed in December of the same year.
VERIFIED REPAIR
Restore the contract rule at the previous anchor January wrap step: use `py, pm = (t.year - 1, 12) if t.month == 1 else (t.year, t.month - 1)`.
Unsuccessful approach: The attempt computes year and month with divmod but keeps the month zero-based, landing one month early.
Case contract
Input {trial_end date, anchor_day 1..28, price}. If trial_end.day equals anchor_day, charge the full price and the next anchor is one month later. Otherwise charge price*days/cycle half-up, where days runs from trial_end to the next anchor date strictly after it and cycle is the length of the anchor-to-anchor month containing trial_end. Return [amount, next anchor ISO].
Why this case matters
Converting a trial onto a fixed billing anchor produces a stub invoice whose length depends on real month boundaries.
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):
t = datetime.date(*x['trial_end'])
a = x['anchor_day']
if t.day == a:
ny, nm = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
return [x['price'], datetime.date(ny, nm, a).isoformat()]
if t.day < a:
nxt = datetime.date(t.year, t.month, a)
py, pm = (t.year, 12) if t.month == 1 else (t.year, t.month - 1)
prev = datetime.date(py, pm, a)
else:
ey, em = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
nxt = datetime.date(ey, em, a)
prev = datetime.date(t.year, t.month, a)
days = (nxt - t).days
cycle = (nxt - prev).days
return [(x['price'] * days * 2 + cycle) // (2 * cycle), nxt.isoformat()]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'trial_end': [2023, 1, 5], 'anchor_day': 28, 'price': 999}, [741, '2023-01-28']), ('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('partial-repair probe', {'trial_end': [2024, 4, 27], 'anchor_day': 28, 'price': 999}, [32, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 12, 16], 'anchor_day': 28, 'price': 2900}, [1160, '2024-12-28']), ('normal control', {'trial_end': [2024, 12, 25], 'anchor_day': 1, 'price': 12600}, [2845, '2025-01-01']), ('normal control', {'trial_end': [2023, 4, 14], 'anchor_day': 1, 'price': 999}, [566, '2023-05-01']), ('normal control', {'trial_end': [2023, 6, 15], 'anchor_day': 15, 'price': 999}, [999, '2023-07-15']), ('normal control', {'trial_end': [2023, 12, 16], 'anchor_day': 15, 'price': 2900}, [2806, '2024-01-15'])], [('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 1], 'anchor_day': 28, 'price': 78891}, [68712, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 6, 4], 'anchor_day': 28, 'price': 999}, [773, '2024-06-28']), ('normal control', {'trial_end': [2025, 3, 15], 'anchor_day': 15, 'price': 2900}, [2900, '2025-04-15']), ('normal control', {'trial_end': [2023, 12, 15], 'anchor_day': 1, 'price': 47732}, [26176, '2024-01-01']), ('normal control', {'trial_end': [2024, 2, 8], 'anchor_day': 8, 'price': 999}, [999, '2024-03-08']), ('normal control', {'trial_end': [2024, 6, 25], 'anchor_day': 1, 'price': 2900}, [580, '2024-07-01'])], [('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 10], 'anchor_day': 15, 'price': 2900}, [468, '2024-04-15']), ('partial-repair probe', {'trial_end': [2023, 10, 3], 'anchor_day': 16, 'price': 999}, [433, '2023-10-16']), ('normal control', {'trial_end': [2023, 12, 26], 'anchor_day': 21, 'price': 999}, [838, '2024-01-21']), ('normal control', {'trial_end': [2023, 5, 26], 'anchor_day': 1, 'price': 62316}, [12061, '2023-06-01']), ('normal control', {'trial_end': [2023, 4, 30], 'anchor_day': 15, 'price': 44760}, [22380, '2023-05-15']), ('normal control', {'trial_end': [2025, 5, 3], 'anchor_day': 1, 'price': 2900}, [2713, '2025-06-01'])], [('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('partial-repair probe', {'trial_end': [2023, 6, 18], 'anchor_day': 28, 'price': 2900}, [935, '2023-06-28']), ('partial-repair probe', {'trial_end': [2025, 3, 22], 'anchor_day': 28, 'price': 58121}, [12455, '2025-03-28']), ('normal control', {'trial_end': [2024, 6, 14], 'anchor_day': 1, 'price': 999}, [566, '2024-07-01']), ('normal control', {'trial_end': [2023, 5, 23], 'anchor_day': 15, 'price': 2900}, [2152, '2023-06-15']), ('normal control', {'trial_end': [2023, 5, 31], 'anchor_day': 4, 'price': 999}, [129, '2023-06-04']), ('normal control', {'trial_end': [2023, 3, 16], 'anchor_day': 15, 'price': 9250}, [8952, '2023-04-15'])], [('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 2360}, [1979, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 3, 15], 'anchor_day': 28, 'price': 999}, [448, '2024-03-28']), ('partial-repair probe', {'trial_end': [2024, 12, 11], 'anchor_day': 15, 'price': 2900}, [387, '2024-12-15']), ('normal control', {'trial_end': [2025, 2, 28], 'anchor_day': 1, 'price': 999}, [36, '2025-03-01']), ('normal control', {'trial_end': [2023, 8, 18], 'anchor_day': 1, 'price': 2900}, [1310, '2023-09-01']), ('normal control', {'trial_end': [2025, 1, 4], 'anchor_day': 1, 'price': 39775}, [35926, '2025-02-01']), ('normal control', {'trial_end': [2024, 7, 15], 'anchor_day': 15, 'price': 999}, [999, '2024-08-15'])]]
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 | [-69, '2023-01-28'] | [741, '2023-01-28'] | Failed |
| regression 1 | [-104, '2025-01-13'] | [1123, '2025-01-13'] | Failed |
| partial-repair probe 2 | [32, '2024-04-28'] | [32, '2024-04-28'] | Passed |
| partial-repair probe 3 | [1160, '2024-12-28'] | [1160, '2024-12-28'] | Passed |
| normal control 4 | [2845, '2025-01-01'] | [2845, '2025-01-01'] | Passed |
| normal control 5 | [566, '2023-05-01'] | [566, '2023-05-01'] | Passed |
| normal control 6 | [999, '2023-07-15'] | [999, '2023-07-15'] | Passed |
| normal control 7 | [2806, '2024-01-15'] | [2806, '2024-01-15'] | Passed |
SHA-256 / 1385c015bf6b8241e0aebc4cf39f26650ece323e6ea6a903801124a1bf4b4a6e
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):
t = datetime.date(*x['trial_end'])
a = x['anchor_day']
if t.day == a:
ny, nm = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
return [x['price'], datetime.date(ny, nm, a).isoformat()]
if t.day < a:
nxt = datetime.date(t.year, t.month, a)
py, pm = divmod(t.year * 12 + t.month - 2, 12)
prev = datetime.date(py, pm, a)
else:
ey, em = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
nxt = datetime.date(ey, em, a)
prev = datetime.date(t.year, t.month, a)
days = (nxt - t).days
cycle = (nxt - prev).days
return [(x['price'] * days * 2 + cycle) // (2 * cycle), nxt.isoformat()]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'trial_end': [2023, 1, 5], 'anchor_day': 28, 'price': 999}, [741, '2023-01-28']), ('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('partial-repair probe', {'trial_end': [2024, 4, 27], 'anchor_day': 28, 'price': 999}, [32, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 12, 16], 'anchor_day': 28, 'price': 2900}, [1160, '2024-12-28']), ('normal control', {'trial_end': [2024, 12, 25], 'anchor_day': 1, 'price': 12600}, [2845, '2025-01-01']), ('normal control', {'trial_end': [2023, 4, 14], 'anchor_day': 1, 'price': 999}, [566, '2023-05-01']), ('normal control', {'trial_end': [2023, 6, 15], 'anchor_day': 15, 'price': 999}, [999, '2023-07-15']), ('normal control', {'trial_end': [2023, 12, 16], 'anchor_day': 15, 'price': 2900}, [2806, '2024-01-15'])], [('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 1], 'anchor_day': 28, 'price': 78891}, [68712, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 6, 4], 'anchor_day': 28, 'price': 999}, [773, '2024-06-28']), ('normal control', {'trial_end': [2025, 3, 15], 'anchor_day': 15, 'price': 2900}, [2900, '2025-04-15']), ('normal control', {'trial_end': [2023, 12, 15], 'anchor_day': 1, 'price': 47732}, [26176, '2024-01-01']), ('normal control', {'trial_end': [2024, 2, 8], 'anchor_day': 8, 'price': 999}, [999, '2024-03-08']), ('normal control', {'trial_end': [2024, 6, 25], 'anchor_day': 1, 'price': 2900}, [580, '2024-07-01'])], [('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 10], 'anchor_day': 15, 'price': 2900}, [468, '2024-04-15']), ('partial-repair probe', {'trial_end': [2023, 10, 3], 'anchor_day': 16, 'price': 999}, [433, '2023-10-16']), ('normal control', {'trial_end': [2023, 12, 26], 'anchor_day': 21, 'price': 999}, [838, '2024-01-21']), ('normal control', {'trial_end': [2023, 5, 26], 'anchor_day': 1, 'price': 62316}, [12061, '2023-06-01']), ('normal control', {'trial_end': [2023, 4, 30], 'anchor_day': 15, 'price': 44760}, [22380, '2023-05-15']), ('normal control', {'trial_end': [2025, 5, 3], 'anchor_day': 1, 'price': 2900}, [2713, '2025-06-01'])], [('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('partial-repair probe', {'trial_end': [2023, 6, 18], 'anchor_day': 28, 'price': 2900}, [935, '2023-06-28']), ('partial-repair probe', {'trial_end': [2025, 3, 22], 'anchor_day': 28, 'price': 58121}, [12455, '2025-03-28']), ('normal control', {'trial_end': [2024, 6, 14], 'anchor_day': 1, 'price': 999}, [566, '2024-07-01']), ('normal control', {'trial_end': [2023, 5, 23], 'anchor_day': 15, 'price': 2900}, [2152, '2023-06-15']), ('normal control', {'trial_end': [2023, 5, 31], 'anchor_day': 4, 'price': 999}, [129, '2023-06-04']), ('normal control', {'trial_end': [2023, 3, 16], 'anchor_day': 15, 'price': 9250}, [8952, '2023-04-15'])], [('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 2360}, [1979, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 3, 15], 'anchor_day': 28, 'price': 999}, [448, '2024-03-28']), ('partial-repair probe', {'trial_end': [2024, 12, 11], 'anchor_day': 15, 'price': 2900}, [387, '2024-12-15']), ('normal control', {'trial_end': [2025, 2, 28], 'anchor_day': 1, 'price': 999}, [36, '2025-03-01']), ('normal control', {'trial_end': [2023, 8, 18], 'anchor_day': 1, 'price': 2900}, [1310, '2023-09-01']), ('normal control', {'trial_end': [2025, 1, 4], 'anchor_day': 1, 'price': 39775}, [35926, '2025-02-01']), ('normal control', {'trial_end': [2024, 7, 15], 'anchor_day': 15, 'price': 999}, [999, '2024-08-15'])]]
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 | [377, '2023-01-28'] | [741, '2023-01-28'] | Failed |
| regression 1 | [570, '2025-01-13'] | [1123, '2025-01-13'] | Failed |
| partial-repair probe 2 | [17, '2024-04-28'] | [32, '2024-04-28'] | Failed |
| partial-repair probe 3 | [570, '2024-12-28'] | [1160, '2024-12-28'] | Failed |
| normal control 4 | [2845, '2025-01-01'] | [2845, '2025-01-01'] | Passed |
| normal control 5 | [566, '2023-05-01'] | [566, '2023-05-01'] | Passed |
| normal control 6 | [999, '2023-07-15'] | [999, '2023-07-15'] | Passed |
| normal control 7 | [2806, '2024-01-15'] | [2806, '2024-01-15'] | Passed |
SHA-256 / fdf3dbef7dc80da51f19447355fae4caa56aa58496912e607e0591705abd9340
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):
t = datetime.date(*x['trial_end'])
a = x['anchor_day']
if t.day == a:
ny, nm = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
return [x['price'], datetime.date(ny, nm, a).isoformat()]
if t.day < a:
nxt = datetime.date(t.year, t.month, a)
py, pm = (t.year - 1, 12) if t.month == 1 else (t.year, t.month - 1)
prev = datetime.date(py, pm, a)
else:
ey, em = (t.year + 1, 1) if t.month == 12 else (t.year, t.month + 1)
nxt = datetime.date(ey, em, a)
prev = datetime.date(t.year, t.month, a)
days = (nxt - t).days
cycle = (nxt - prev).days
return [(x['price'] * days * 2 + cycle) // (2 * cycle), nxt.isoformat()]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'trial_end': [2023, 1, 5], 'anchor_day': 28, 'price': 999}, [741, '2023-01-28']), ('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('partial-repair probe', {'trial_end': [2024, 4, 27], 'anchor_day': 28, 'price': 999}, [32, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 12, 16], 'anchor_day': 28, 'price': 2900}, [1160, '2024-12-28']), ('normal control', {'trial_end': [2024, 12, 25], 'anchor_day': 1, 'price': 12600}, [2845, '2025-01-01']), ('normal control', {'trial_end': [2023, 4, 14], 'anchor_day': 1, 'price': 999}, [566, '2023-05-01']), ('normal control', {'trial_end': [2023, 6, 15], 'anchor_day': 15, 'price': 999}, [999, '2023-07-15']), ('normal control', {'trial_end': [2023, 12, 16], 'anchor_day': 15, 'price': 2900}, [2806, '2024-01-15'])], [('regression', {'trial_end': [2025, 1, 1], 'anchor_day': 13, 'price': 2900}, [1123, '2025-01-13']), ('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 1], 'anchor_day': 28, 'price': 78891}, [68712, '2024-04-28']), ('partial-repair probe', {'trial_end': [2024, 6, 4], 'anchor_day': 28, 'price': 999}, [773, '2024-06-28']), ('normal control', {'trial_end': [2025, 3, 15], 'anchor_day': 15, 'price': 2900}, [2900, '2025-04-15']), ('normal control', {'trial_end': [2023, 12, 15], 'anchor_day': 1, 'price': 47732}, [26176, '2024-01-01']), ('normal control', {'trial_end': [2024, 2, 8], 'anchor_day': 8, 'price': 999}, [999, '2024-03-08']), ('normal control', {'trial_end': [2024, 6, 25], 'anchor_day': 1, 'price': 2900}, [580, '2024-07-01'])], [('regression', {'trial_end': [2024, 1, 1], 'anchor_day': 28, 'price': 2900}, [2526, '2024-01-28']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 4, 10], 'anchor_day': 15, 'price': 2900}, [468, '2024-04-15']), ('partial-repair probe', {'trial_end': [2023, 10, 3], 'anchor_day': 16, 'price': 999}, [433, '2023-10-16']), ('normal control', {'trial_end': [2023, 12, 26], 'anchor_day': 21, 'price': 999}, [838, '2024-01-21']), ('normal control', {'trial_end': [2023, 5, 26], 'anchor_day': 1, 'price': 62316}, [12061, '2023-06-01']), ('normal control', {'trial_end': [2023, 4, 30], 'anchor_day': 15, 'price': 44760}, [22380, '2023-05-15']), ('normal control', {'trial_end': [2025, 5, 3], 'anchor_day': 1, 'price': 2900}, [2713, '2025-06-01'])], [('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 999}, [838, '2025-01-28']), ('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('partial-repair probe', {'trial_end': [2023, 6, 18], 'anchor_day': 28, 'price': 2900}, [935, '2023-06-28']), ('partial-repair probe', {'trial_end': [2025, 3, 22], 'anchor_day': 28, 'price': 58121}, [12455, '2025-03-28']), ('normal control', {'trial_end': [2024, 6, 14], 'anchor_day': 1, 'price': 999}, [566, '2024-07-01']), ('normal control', {'trial_end': [2023, 5, 23], 'anchor_day': 15, 'price': 2900}, [2152, '2023-06-15']), ('normal control', {'trial_end': [2023, 5, 31], 'anchor_day': 4, 'price': 999}, [129, '2023-06-04']), ('normal control', {'trial_end': [2023, 3, 16], 'anchor_day': 15, 'price': 9250}, [8952, '2023-04-15'])], [('regression', {'trial_end': [2024, 1, 7], 'anchor_day': 15, 'price': 28964}, [7475, '2024-01-15']), ('regression', {'trial_end': [2025, 1, 2], 'anchor_day': 28, 'price': 2360}, [1979, '2025-01-28']), ('partial-repair probe', {'trial_end': [2024, 3, 15], 'anchor_day': 28, 'price': 999}, [448, '2024-03-28']), ('partial-repair probe', {'trial_end': [2024, 12, 11], 'anchor_day': 15, 'price': 2900}, [387, '2024-12-15']), ('normal control', {'trial_end': [2025, 2, 28], 'anchor_day': 1, 'price': 999}, [36, '2025-03-01']), ('normal control', {'trial_end': [2023, 8, 18], 'anchor_day': 1, 'price': 2900}, [1310, '2023-09-01']), ('normal control', {'trial_end': [2025, 1, 4], 'anchor_day': 1, 'price': 39775}, [35926, '2025-02-01']), ('normal control', {'trial_end': [2024, 7, 15], 'anchor_day': 15, 'price': 999}, [999, '2024-08-15'])]]
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 | [741, '2023-01-28'] | [741, '2023-01-28'] | Passed |
| regression 1 | [1123, '2025-01-13'] | [1123, '2025-01-13'] | Passed |
| partial-repair probe 2 | [32, '2024-04-28'] | [32, '2024-04-28'] | Passed |
| partial-repair probe 3 | [1160, '2024-12-28'] | [1160, '2024-12-28'] | Passed |
| normal control 4 | [2845, '2025-01-01'] | [2845, '2025-01-01'] | Passed |
| normal control 5 | [566, '2023-05-01'] | [566, '2023-05-01'] | Passed |
| normal control 6 | [999, '2023-07-15'] | [999, '2023-07-15'] | Passed |
| normal control 7 | [2806, '2024-01-15'] | [2806, '2024-01-15'] | Passed |
SHA-256 / 28149ef1c434403d3803c9d2ba00915ff6c205e739155fe165bb22a97b9ace43
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 2026-09-29T14:46:36.217387+00:00.
Case digest / 09b2f0f51fcfdb6be4dd9c0465c12a82cb5bdd97d2ef8361b8b874d1fcb5186c