FA-94076 / Shift rostering labor rules / Open access
Partial school weeks treated as vacation weeks · case 01
A three-day school week allows 40 hours of work.
ROOT CAUSE
The school-week cap applies only when all five weekdays are school days.
VERIFIED REPAIR
Any school day in the week makes it a school week.
Unsuccessful approach: Requiring four school days still lets short school weeks use the vacation cap.
Case contract
Toy youth rule: age 16 or older has no restrictions. Otherwise each shift [day, start, end] must lie within 07:00-19:00 (start >= 420, end <= 1140); daily total minutes may not exceed 180 on a listed school day or 480 otherwise; the weekly total may not exceed 1080 if the week has any school day, else 2400. Return window violations in shift order, then daily caps by day, then the weekly cap as ["weekly_cap", -1].
Why this case matters
Minor-worker hour limits are strict roster constraints with many boundary conditions.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(age, shifts, school_days):
if age >= 16:
return []
out = []
per = {}
for d, st, en in shifts:
per[d] = per.get(d, 0) + en - st
if st < 420 or en > 1140:
out.append(['hours_window', d])
for d in sorted(per):
cap = 180 if d in school_days else 480
if per[d] > cap:
out.append(['daily_cap', d])
week_cap = 1080 if len(school_days) >= 5 else 2400
if sum(per.values()) > week_cap:
out.append(['weekly_cap', -1])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: school week detection 1',
[14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]], [['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[6, 900, 1380], [0, 480, 960], [0, 1020, 1201], [0, 900, 1080], [5, 420, 540], [0, 960, 1260]],
[0, 3, 5, 6]],
[['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[4, 1080, 1320], [3, 1080, 1440], [4, 900, 1380], [4, 1080, 1140]], [2, 3, 4]],
[['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4],
['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('boundary control 5', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('normal control 6',
[15, [[1, 900, 1380], [4, 360, 600], [1, 960, 1440], [3, 900, 960], [2, 360, 540]], []],
[['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]]),
('normal control 7',
[16, [[6, 1080, 1380], [1, 1020, 1440], [1, 360, 420], [1, 1020, 1200]], [0, 1, 3, 5, 6]], []),
('normal control 8',
[17, [[6, 419, 719], [2, 900, 1200], [4, 419, 600], [5, 480, 661], [2, 1080, 1440], [0, 960, 1141]],
[0, 1, 2, 3, 5]],
[])],
[('regression: school week detection 1',
[15, [[6, 900, 1020], [3, 1080, 1380], [2, 1080, 1200], [0, 1080, 1380], [5, 480, 780]], [0, 1, 5, 6]],
[['hours_window', 3], ['hours_window', 2], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 5],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[6, 1020, 1140], [3, 419, 479], [2, 480, 960], [4, 1020, 1320], [4, 1080, 1200], [1, 360, 540]],
[0, 1, 3, 4]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 4], ['hours_window', 1], ['daily_cap', 4],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 1080, 1320], [6, 960, 1260], [3, 900, 1080], [6, 960, 1260], [4, 480, 780], [4, 900, 1081]],
[2, 4, 6]],
[['hours_window', 6], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4], ['daily_cap', 6],
['weekly_cap', -1]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('boundary control 5', [16, [[0, 300, 1300]], [0]], []),
('normal control 6',
[17, [[5, 360, 541], [5, 900, 1080], [6, 360, 540], [4, 420, 600], [0, 900, 960], [1, 960, 1020]],
[0, 1, 5]],
[]),
('normal control 7',
[14, [[1, 900, 960], [1, 360, 541], [0, 480, 661], [5, 420, 480], [4, 360, 541], [0, 900, 960]], []],
[['hours_window', 1], ['hours_window', 4]]),
('normal control 8',
[15, [[0, 900, 960], [3, 480, 661], [1, 900, 960], [2, 1020, 1201], [6, 419, 659]], [0, 2, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[15, [[3, 420, 480], [5, 480, 960], [5, 1020, 1320], [1, 1080, 1200], [3, 419, 600], [5, 419, 599]],
[1, 3, 4]],
[['hours_window', 5], ['hours_window', 1], ['hours_window', 3], ['hours_window', 5], ['daily_cap', 3],
['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 960, 1440], [1, 1020, 1260], [2, 360, 541], [0, 360, 840], [3, 960, 1141], [0, 1020, 1080]],
[1, 2, 4]],
[['hours_window', 6], ['hours_window', 1], ['hours_window', 2], ['hours_window', 0], ['hours_window', 3],
['daily_cap', 0], ['daily_cap', 1], ['daily_cap', 2], ['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1140]], []], []),
('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
('normal control 6',
[15, [[0, 960, 1260], [1, 960, 1440], [5, 419, 899], [0, 900, 1140], [5, 360, 420]], [1, 2, 4, 5, 6]],
[['hours_window', 0], ['hours_window', 1], ['hours_window', 5], ['hours_window', 5], ['daily_cap', 0],
['daily_cap', 1], ['daily_cap', 5], ['weekly_cap', -1]]),
('normal control 7', [17, [[2, 1080, 1320], [2, 960, 1140], [6, 480, 720], [0, 960, 1140]], [1, 2, 5]], []),
('normal control 8', [14, [[4, 900, 1080], [4, 1020, 1320], [4, 480, 780], [0, 360, 480]], [0, 2, 4, 5, 6]],
[['hours_window', 4], ['hours_window', 0], ['daily_cap', 4]])],
[('regression: school week detection 1',
[14, [[5, 1020, 1320], [2, 419, 659], [2, 1020, 1200], [3, 1020, 1260], [5, 1080, 1261], [6, 900, 960]],
[0, 3, 5, 6]],
[['hours_window', 5], ['hours_window', 2], ['hours_window', 2], ['hours_window', 3], ['hours_window', 5],
['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[4, 900, 1081], [2, 419, 600], [5, 360, 540], [6, 960, 1440], [6, 1020, 1260]], [3, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 5], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4],
['daily_cap', 6], ['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]]),
('boundary control 4', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
('boundary control 5', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('normal control 6', [15, [[3, 900, 1081], [6, 900, 1200], [0, 420, 600]], []], [['hours_window', 6]]),
('normal control 7',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('normal control 8',
[14, [[4, 1020, 1320], [2, 1020, 1320], [6, 900, 960], [6, 1020, 1440]], [0, 1, 2, 5, 6]],
[['hours_window', 4], ['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('boundary control 3', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('normal control 5',
[14, [[4, 1080, 1380], [6, 1020, 1140], [1, 1020, 1200], [6, 480, 540]], [0, 2, 3, 4, 6]],
[['hours_window', 4], ['hours_window', 1], ['daily_cap', 4]]),
('normal control 6', [15, [[2, 1080, 1200], [2, 1020, 1080], [1, 1080, 1320]], [1, 2, 3, 4]],
[['hours_window', 2], ['hours_window', 1], ['daily_cap', 1]]),
('normal control 7', [14, [[2, 360, 660]], []], [['hours_window', 2]]),
('normal control 8',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]])]]
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: school week detection 1 | [] | [['weekly_cap', -1]] | Failed |
| regression variant: school week detection 2 | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6]] | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6], ['weekly_cap', -1]] | Failed |
| partial repair guard 3 | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4]] | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]] | Failed |
| boundary control 4 | [['hours_window', 5]] | [['hours_window', 5]] | Passed |
| boundary control 5 | [['daily_cap', 0]] | [['daily_cap', 0]] | Passed |
| normal control 6 | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | Passed |
| normal control 7 | [] | [] | Passed |
| normal control 8 | [] | [] | Passed |
SHA-256 / 288d8663d8901b5441cb0457fb5666c82c9cb55561405503dc6e8030544947ab
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(age, shifts, school_days):
if age >= 16:
return []
out = []
per = {}
for d, st, en in shifts:
per[d] = per.get(d, 0) + en - st
if st < 420 or en > 1140:
out.append(['hours_window', d])
for d in sorted(per):
cap = 180 if d in school_days else 480
if per[d] > cap:
out.append(['daily_cap', d])
week_cap = 1080 if len(school_days) > 3 else 2400
if sum(per.values()) > week_cap:
out.append(['weekly_cap', -1])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: school week detection 1',
[14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]], [['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[6, 900, 1380], [0, 480, 960], [0, 1020, 1201], [0, 900, 1080], [5, 420, 540], [0, 960, 1260]],
[0, 3, 5, 6]],
[['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[4, 1080, 1320], [3, 1080, 1440], [4, 900, 1380], [4, 1080, 1140]], [2, 3, 4]],
[['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4],
['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('boundary control 5', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('normal control 6',
[15, [[1, 900, 1380], [4, 360, 600], [1, 960, 1440], [3, 900, 960], [2, 360, 540]], []],
[['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]]),
('normal control 7',
[16, [[6, 1080, 1380], [1, 1020, 1440], [1, 360, 420], [1, 1020, 1200]], [0, 1, 3, 5, 6]], []),
('normal control 8',
[17, [[6, 419, 719], [2, 900, 1200], [4, 419, 600], [5, 480, 661], [2, 1080, 1440], [0, 960, 1141]],
[0, 1, 2, 3, 5]],
[])],
[('regression: school week detection 1',
[15, [[6, 900, 1020], [3, 1080, 1380], [2, 1080, 1200], [0, 1080, 1380], [5, 480, 780]], [0, 1, 5, 6]],
[['hours_window', 3], ['hours_window', 2], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 5],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[6, 1020, 1140], [3, 419, 479], [2, 480, 960], [4, 1020, 1320], [4, 1080, 1200], [1, 360, 540]],
[0, 1, 3, 4]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 4], ['hours_window', 1], ['daily_cap', 4],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 1080, 1320], [6, 960, 1260], [3, 900, 1080], [6, 960, 1260], [4, 480, 780], [4, 900, 1081]],
[2, 4, 6]],
[['hours_window', 6], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4], ['daily_cap', 6],
['weekly_cap', -1]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('boundary control 5', [16, [[0, 300, 1300]], [0]], []),
('normal control 6',
[17, [[5, 360, 541], [5, 900, 1080], [6, 360, 540], [4, 420, 600], [0, 900, 960], [1, 960, 1020]],
[0, 1, 5]],
[]),
('normal control 7',
[14, [[1, 900, 960], [1, 360, 541], [0, 480, 661], [5, 420, 480], [4, 360, 541], [0, 900, 960]], []],
[['hours_window', 1], ['hours_window', 4]]),
('normal control 8',
[15, [[0, 900, 960], [3, 480, 661], [1, 900, 960], [2, 1020, 1201], [6, 419, 659]], [0, 2, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[15, [[3, 420, 480], [5, 480, 960], [5, 1020, 1320], [1, 1080, 1200], [3, 419, 600], [5, 419, 599]],
[1, 3, 4]],
[['hours_window', 5], ['hours_window', 1], ['hours_window', 3], ['hours_window', 5], ['daily_cap', 3],
['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 960, 1440], [1, 1020, 1260], [2, 360, 541], [0, 360, 840], [3, 960, 1141], [0, 1020, 1080]],
[1, 2, 4]],
[['hours_window', 6], ['hours_window', 1], ['hours_window', 2], ['hours_window', 0], ['hours_window', 3],
['daily_cap', 0], ['daily_cap', 1], ['daily_cap', 2], ['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1140]], []], []),
('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
('normal control 6',
[15, [[0, 960, 1260], [1, 960, 1440], [5, 419, 899], [0, 900, 1140], [5, 360, 420]], [1, 2, 4, 5, 6]],
[['hours_window', 0], ['hours_window', 1], ['hours_window', 5], ['hours_window', 5], ['daily_cap', 0],
['daily_cap', 1], ['daily_cap', 5], ['weekly_cap', -1]]),
('normal control 7', [17, [[2, 1080, 1320], [2, 960, 1140], [6, 480, 720], [0, 960, 1140]], [1, 2, 5]], []),
('normal control 8', [14, [[4, 900, 1080], [4, 1020, 1320], [4, 480, 780], [0, 360, 480]], [0, 2, 4, 5, 6]],
[['hours_window', 4], ['hours_window', 0], ['daily_cap', 4]])],
[('regression: school week detection 1',
[14, [[5, 1020, 1320], [2, 419, 659], [2, 1020, 1200], [3, 1020, 1260], [5, 1080, 1261], [6, 900, 960]],
[0, 3, 5, 6]],
[['hours_window', 5], ['hours_window', 2], ['hours_window', 2], ['hours_window', 3], ['hours_window', 5],
['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[4, 900, 1081], [2, 419, 600], [5, 360, 540], [6, 960, 1440], [6, 1020, 1260]], [3, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 5], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4],
['daily_cap', 6], ['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]]),
('boundary control 4', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
('boundary control 5', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('normal control 6', [15, [[3, 900, 1081], [6, 900, 1200], [0, 420, 600]], []], [['hours_window', 6]]),
('normal control 7',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('normal control 8',
[14, [[4, 1020, 1320], [2, 1020, 1320], [6, 900, 960], [6, 1020, 1440]], [0, 1, 2, 5, 6]],
[['hours_window', 4], ['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('boundary control 3', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('normal control 5',
[14, [[4, 1080, 1380], [6, 1020, 1140], [1, 1020, 1200], [6, 480, 540]], [0, 2, 3, 4, 6]],
[['hours_window', 4], ['hours_window', 1], ['daily_cap', 4]]),
('normal control 6', [15, [[2, 1080, 1200], [2, 1020, 1080], [1, 1080, 1320]], [1, 2, 3, 4]],
[['hours_window', 2], ['hours_window', 1], ['daily_cap', 1]]),
('normal control 7', [14, [[2, 360, 660]], []], [['hours_window', 2]]),
('normal control 8',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]])]]
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: school week detection 1 | [] | [['weekly_cap', -1]] | Failed |
| regression variant: school week detection 2 | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6], ['weekly_cap', -1]] | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6], ['weekly_cap', -1]] | Passed |
| partial repair guard 3 | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4]] | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]] | Failed |
| boundary control 4 | [['hours_window', 5]] | [['hours_window', 5]] | Passed |
| boundary control 5 | [['daily_cap', 0]] | [['daily_cap', 0]] | Passed |
| normal control 6 | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | Passed |
| normal control 7 | [] | [] | Passed |
| normal control 8 | [] | [] | Passed |
SHA-256 / c671f279af3aeee628e35e44822ed02e3f6a78efa276979f2e2557838fa1615f
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(age, shifts, school_days):
if age >= 16:
return []
out = []
per = {}
for d, st, en in shifts:
per[d] = per.get(d, 0) + en - st
if st < 420 or en > 1140:
out.append(['hours_window', d])
for d in sorted(per):
cap = 180 if d in school_days else 480
if per[d] > cap:
out.append(['daily_cap', d])
week_cap = 1080 if school_days else 2400
if sum(per.values()) > week_cap:
out.append(['weekly_cap', -1])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: school week detection 1',
[14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]], [['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[6, 900, 1380], [0, 480, 960], [0, 1020, 1201], [0, 900, 1080], [5, 420, 540], [0, 960, 1260]],
[0, 3, 5, 6]],
[['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[4, 1080, 1320], [3, 1080, 1440], [4, 900, 1380], [4, 1080, 1140]], [2, 3, 4]],
[['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4],
['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('boundary control 5', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('normal control 6',
[15, [[1, 900, 1380], [4, 360, 600], [1, 960, 1440], [3, 900, 960], [2, 360, 540]], []],
[['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]]),
('normal control 7',
[16, [[6, 1080, 1380], [1, 1020, 1440], [1, 360, 420], [1, 1020, 1200]], [0, 1, 3, 5, 6]], []),
('normal control 8',
[17, [[6, 419, 719], [2, 900, 1200], [4, 419, 600], [5, 480, 661], [2, 1080, 1440], [0, 960, 1141]],
[0, 1, 2, 3, 5]],
[])],
[('regression: school week detection 1',
[15, [[6, 900, 1020], [3, 1080, 1380], [2, 1080, 1200], [0, 1080, 1380], [5, 480, 780]], [0, 1, 5, 6]],
[['hours_window', 3], ['hours_window', 2], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 5],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[6, 1020, 1140], [3, 419, 479], [2, 480, 960], [4, 1020, 1320], [4, 1080, 1200], [1, 360, 540]],
[0, 1, 3, 4]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 4], ['hours_window', 1], ['daily_cap', 4],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 1080, 1320], [6, 960, 1260], [3, 900, 1080], [6, 960, 1260], [4, 480, 780], [4, 900, 1081]],
[2, 4, 6]],
[['hours_window', 6], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4], ['daily_cap', 6],
['weekly_cap', -1]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('boundary control 5', [16, [[0, 300, 1300]], [0]], []),
('normal control 6',
[17, [[5, 360, 541], [5, 900, 1080], [6, 360, 540], [4, 420, 600], [0, 900, 960], [1, 960, 1020]],
[0, 1, 5]],
[]),
('normal control 7',
[14, [[1, 900, 960], [1, 360, 541], [0, 480, 661], [5, 420, 480], [4, 360, 541], [0, 900, 960]], []],
[['hours_window', 1], ['hours_window', 4]]),
('normal control 8',
[15, [[0, 900, 960], [3, 480, 661], [1, 900, 960], [2, 1020, 1201], [6, 419, 659]], [0, 2, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[15, [[3, 420, 480], [5, 480, 960], [5, 1020, 1320], [1, 1080, 1200], [3, 419, 600], [5, 419, 599]],
[1, 3, 4]],
[['hours_window', 5], ['hours_window', 1], ['hours_window', 3], ['hours_window', 5], ['daily_cap', 3],
['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[6, 960, 1440], [1, 1020, 1260], [2, 360, 541], [0, 360, 840], [3, 960, 1141], [0, 1020, 1080]],
[1, 2, 4]],
[['hours_window', 6], ['hours_window', 1], ['hours_window', 2], ['hours_window', 0], ['hours_window', 3],
['daily_cap', 0], ['daily_cap', 1], ['daily_cap', 2], ['weekly_cap', -1]]),
('boundary control 4', [15, [[5, 960, 1140]], []], []),
('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
('normal control 6',
[15, [[0, 960, 1260], [1, 960, 1440], [5, 419, 899], [0, 900, 1140], [5, 360, 420]], [1, 2, 4, 5, 6]],
[['hours_window', 0], ['hours_window', 1], ['hours_window', 5], ['hours_window', 5], ['daily_cap', 0],
['daily_cap', 1], ['daily_cap', 5], ['weekly_cap', -1]]),
('normal control 7', [17, [[2, 1080, 1320], [2, 960, 1140], [6, 480, 720], [0, 960, 1140]], [1, 2, 5]], []),
('normal control 8', [14, [[4, 900, 1080], [4, 1020, 1320], [4, 480, 780], [0, 360, 480]], [0, 2, 4, 5, 6]],
[['hours_window', 4], ['hours_window', 0], ['daily_cap', 4]])],
[('regression: school week detection 1',
[14, [[5, 1020, 1320], [2, 419, 659], [2, 1020, 1200], [3, 1020, 1260], [5, 1080, 1261], [6, 900, 960]],
[0, 3, 5, 6]],
[['hours_window', 5], ['hours_window', 2], ['hours_window', 2], ['hours_window', 3], ['hours_window', 5],
['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
('regression variant: school week detection 2',
[15, [[4, 900, 1081], [2, 419, 600], [5, 360, 540], [6, 960, 1440], [6, 1020, 1260]], [3, 4, 5, 6]],
[['hours_window', 2], ['hours_window', 5], ['hours_window', 6], ['hours_window', 6], ['daily_cap', 4],
['daily_cap', 6], ['weekly_cap', -1]]),
('partial repair guard 3',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]]),
('boundary control 4', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
('boundary control 5', [15, [[5, 960, 1141]], []], [['hours_window', 5]]),
('normal control 6', [15, [[3, 900, 1081], [6, 900, 1200], [0, 420, 600]], []], [['hours_window', 6]]),
('normal control 7',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('normal control 8',
[14, [[4, 1020, 1320], [2, 1020, 1320], [6, 900, 960], [6, 1020, 1440]], [0, 1, 2, 5, 6]],
[['hours_window', 4], ['hours_window', 2], ['hours_window', 6], ['daily_cap', 2], ['daily_cap', 6]])],
[('regression: school week detection 1',
[14, [[5, 960, 1141], [6, 1080, 1261], [0, 480, 780], [5, 360, 600], [6, 420, 601], [4, 960, 1080]],
[0, 1, 3, 6]],
[['hours_window', 5], ['hours_window', 6], ['hours_window', 5], ['daily_cap', 0], ['daily_cap', 6],
['weekly_cap', -1]]),
('regression variant: school week detection 2',
[14, [[4, 360, 600], [5, 420, 601], [6, 900, 1200], [3, 360, 660], [6, 360, 480]], [3, 4, 6]],
[['hours_window', 4], ['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['daily_cap', 3],
['daily_cap', 4], ['daily_cap', 6], ['weekly_cap', -1]]),
('boundary control 3', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
('boundary control 4', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
[['weekly_cap', -1]]),
('normal control 5',
[14, [[4, 1080, 1380], [6, 1020, 1140], [1, 1020, 1200], [6, 480, 540]], [0, 2, 3, 4, 6]],
[['hours_window', 4], ['hours_window', 1], ['daily_cap', 4]]),
('normal control 6', [15, [[2, 1080, 1200], [2, 1020, 1080], [1, 1080, 1320]], [1, 2, 3, 4]],
[['hours_window', 2], ['hours_window', 1], ['daily_cap', 1]]),
('normal control 7', [14, [[2, 360, 660]], []], [['hours_window', 2]]),
('normal control 8',
[15, [[3, 900, 1380], [4, 1080, 1200], [6, 419, 539], [4, 1080, 1440], [5, 480, 780]], [0, 3, 6]],
[['hours_window', 3], ['hours_window', 4], ['hours_window', 6], ['hours_window', 4], ['daily_cap', 3],
['weekly_cap', -1]])]]
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: school week detection 1 | [['weekly_cap', -1]] | [['weekly_cap', -1]] | Passed |
| regression variant: school week detection 2 | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6], ['weekly_cap', -1]] | [['hours_window', 6], ['hours_window', 0], ['hours_window', 0], ['daily_cap', 0], ['daily_cap', 6], ['weekly_cap', -1]] | Passed |
| partial repair guard 3 | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]] | [['hours_window', 4], ['hours_window', 3], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]] | Passed |
| boundary control 4 | [['hours_window', 5]] | [['hours_window', 5]] | Passed |
| boundary control 5 | [['daily_cap', 0]] | [['daily_cap', 0]] | Passed |
| normal control 6 | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | [['hours_window', 1], ['hours_window', 4], ['hours_window', 1], ['hours_window', 2], ['daily_cap', 1]] | Passed |
| normal control 7 | [] | [] | Passed |
| normal control 8 | [] | [] | Passed |
SHA-256 / a71c5f87bf037797f46b417ebd51341a5dd5ee2db96228248b9773a9d7948173
Verification & scope
Stipulated toy labor rule for a bounded roster model; it is not legal advice and does not claim conformance with any jurisdiction, award, or collective agreement. 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 2026-09-29T14:52:00.920587+00:00.
Case digest / 06c71ba0442bd382a1e07fc4072f942b678a1b42bd3c734ae3e6286c75b42688