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FA-94066 / Shift rostering labor rules / Open access

Daily cap checks only the last shift of the day · case 01

Two short shifts on a school day exceed three hours without a finding.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Daily minutes are overwritten per shift instead of accumulated.

VERIFIED REPAIR

Sum all shift minutes per day.

Unsuccessful approach: Keeping the longest shift still ignores split days.

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] = 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: daily total aggregation 1', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [15, [[0, 1020, 1200], [3, 1020, 1200], [1, 360, 540], [1, 420, 480], [4, 419, 599], [1, 900, 960]],
    [0, 1, 2, 3, 6]],
   [['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [15, [[1, 419, 599], [5, 1020, 1320], [1, 480, 720], [5, 420, 480], [2, 360, 600], [1, 1020, 1201]],
    [0, 3, 4, 5, 6]],
   [['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1],
    ['daily_cap', 5], ['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, 1200]], []], [['hours_window', 1]]),
  ('normal control 7',
   [15, [[3, 900, 1200], [1, 1020, 1201], [3, 900, 1081], [1, 419, 719], [4, 1080, 1261], [2, 960, 1020]],
    [0, 2, 3, 4, 5]],
   [['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1],
    ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]),
  ('normal control 8',
   [17, [[3, 1080, 1200], [2, 900, 1200], [6, 420, 480], [3, 1080, 1380], [2, 960, 1200]], [0, 2, 4]], [])],
 [('regression: daily total aggregation 1',
   [15, [[5, 1020, 1200], [5, 900, 960], [5, 360, 480], [5, 420, 600], [6, 360, 840], [0, 480, 660]], []],
   [['hours_window', 5], ['hours_window', 5], ['hours_window', 6], ['daily_cap', 5]]),
  ('regression variant: daily total aggregation 2',
   [15, [[6, 480, 660], [5, 420, 600], [1, 480, 660], [1, 360, 480]], [1, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [14, [[5, 480, 960], [0, 480, 960], [6, 960, 1200], [6, 960, 1260], [5, 900, 1020]], []],
   [['hours_window', 6], ['hours_window', 6], ['daily_cap', 5], ['daily_cap', 6]]),
  ('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',
   [15, [[0, 1020, 1080], [6, 1020, 1260], [3, 1020, 1320], [6, 480, 660], [2, 480, 960]], []],
   [['hours_window', 6], ['hours_window', 3]]),
  ('normal control 7',
   [17, [[1, 420, 601], [2, 1020, 1200], [0, 960, 1140], [0, 1080, 1320]], [0, 2, 3, 5, 6]], []),
  ('normal control 8', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], [])],
 [('regression: daily total aggregation 1', [14, [[1, 420, 601], [1, 960, 1260]], [0, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [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]]),
  ('partial repair guard 3',
   [15, [[3, 419, 599], [3, 900, 1081], [2, 360, 660], [3, 360, 660], [2, 419, 719]], []],
   [['hours_window', 3], ['hours_window', 2], ['hours_window', 3], ['hours_window', 2], ['daily_cap', 2],
    ['daily_cap', 3]]),
  ('boundary control 4', [15, [[5, 960, 1140]], []], []),
  ('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
  ('normal control 6', [16, [[1, 480, 960], [1, 420, 660]], [0, 3, 5, 6]], []),
  ('normal control 7', [17, [[2, 1080, 1260], [0, 419, 719]], [2, 4, 6]], []),
  ('normal control 8', [15, [[3, 419, 599], [4, 360, 420]], [3, 4, 5]],
   [['hours_window', 3], ['hours_window', 4]])],
 [('regression: daily total aggregation 1',
   [15, [[6, 360, 541], [1, 900, 960], [5, 480, 600], [1, 420, 660], [4, 900, 1020], [1, 1020, 1140]],
    [0, 1, 4, 5]],
   [['hours_window', 6], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [14, [[2, 360, 660], [6, 1080, 1380], [0, 1020, 1260], [2, 1080, 1200], [3, 420, 660], [5, 480, 661]],
    [0, 1, 2, 3, 5]],
   [['hours_window', 2], ['hours_window', 6], ['hours_window', 0], ['hours_window', 2], ['daily_cap', 0],
    ['daily_cap', 2], ['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
  ('partial repair guard 3',
   [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]]),
  ('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', [17, [[3, 900, 960], [3, 1020, 1260]], [0, 1, 2, 4, 5]], []),
  ('normal control 7', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], []),
  ('normal control 8', [16, [[3, 360, 541], [5, 1020, 1080], [0, 1080, 1260], [1, 420, 601]], []], [])],
 [('regression: daily total aggregation 1', [15, [[3, 960, 1141], [3, 1020, 1440]], [0, 2, 4, 5, 6]],
   [['hours_window', 3], ['hours_window', 3], ['daily_cap', 3]]),
  ('regression variant: daily total aggregation 2',
   [14, [[6, 900, 960], [0, 1080, 1440], [5, 419, 659], [0, 1020, 1080]], [0, 1, 3]],
   [['hours_window', 0], ['hours_window', 5], ['daily_cap', 0]]),
  ('partial repair guard 3',
   [15, [[1, 480, 660], [1, 1080, 1140], [1, 419, 479], [4, 1080, 1260]], [0, 1, 2, 5]],
   [['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('boundary control 4', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
  ('boundary control 5', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
   [['weekly_cap', -1]]),
  ('normal control 6', [14, [[2, 1080, 1380], [0, 420, 540], [6, 960, 1020]], [0, 1, 2, 3, 6]],
   [['hours_window', 2], ['daily_cap', 2]]),
  ('normal control 7',
   [15, [[5, 1080, 1140], [6, 419, 719], [3, 1080, 1200], [6, 419, 479], [4, 1020, 1200]], [0, 1, 2, 4]],
   [['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['hours_window', 4]]),
  ('normal control 8', [17, [[5, 900, 1081], [5, 1020, 1200], [0, 1080, 1261], [3, 960, 1080]], []], [])]]
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 fixtureActualExpectedOutcome
regression: daily total aggregation 1[][['daily_cap', 1]]Failed
regression variant: daily total aggregation 2[['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4]][['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]Failed
partial repair guard 3[['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1]][['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1], ['daily_cap', 5], ['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', 1]]Passed
normal control 7[['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4]][['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]Failed
normal control 8[][]Passed

SHA-256 / 2cb2f8e9f2e44f13c47e14e85ff01551a895916fe9696dc46d693d65c6c2ee6f

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] = max(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: daily total aggregation 1', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [15, [[0, 1020, 1200], [3, 1020, 1200], [1, 360, 540], [1, 420, 480], [4, 419, 599], [1, 900, 960]],
    [0, 1, 2, 3, 6]],
   [['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [15, [[1, 419, 599], [5, 1020, 1320], [1, 480, 720], [5, 420, 480], [2, 360, 600], [1, 1020, 1201]],
    [0, 3, 4, 5, 6]],
   [['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1],
    ['daily_cap', 5], ['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, 1200]], []], [['hours_window', 1]]),
  ('normal control 7',
   [15, [[3, 900, 1200], [1, 1020, 1201], [3, 900, 1081], [1, 419, 719], [4, 1080, 1261], [2, 960, 1020]],
    [0, 2, 3, 4, 5]],
   [['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1],
    ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]),
  ('normal control 8',
   [17, [[3, 1080, 1200], [2, 900, 1200], [6, 420, 480], [3, 1080, 1380], [2, 960, 1200]], [0, 2, 4]], [])],
 [('regression: daily total aggregation 1',
   [15, [[5, 1020, 1200], [5, 900, 960], [5, 360, 480], [5, 420, 600], [6, 360, 840], [0, 480, 660]], []],
   [['hours_window', 5], ['hours_window', 5], ['hours_window', 6], ['daily_cap', 5]]),
  ('regression variant: daily total aggregation 2',
   [15, [[6, 480, 660], [5, 420, 600], [1, 480, 660], [1, 360, 480]], [1, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [14, [[5, 480, 960], [0, 480, 960], [6, 960, 1200], [6, 960, 1260], [5, 900, 1020]], []],
   [['hours_window', 6], ['hours_window', 6], ['daily_cap', 5], ['daily_cap', 6]]),
  ('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',
   [15, [[0, 1020, 1080], [6, 1020, 1260], [3, 1020, 1320], [6, 480, 660], [2, 480, 960]], []],
   [['hours_window', 6], ['hours_window', 3]]),
  ('normal control 7',
   [17, [[1, 420, 601], [2, 1020, 1200], [0, 960, 1140], [0, 1080, 1320]], [0, 2, 3, 5, 6]], []),
  ('normal control 8', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], [])],
 [('regression: daily total aggregation 1', [14, [[1, 420, 601], [1, 960, 1260]], [0, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [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]]),
  ('partial repair guard 3',
   [15, [[3, 419, 599], [3, 900, 1081], [2, 360, 660], [3, 360, 660], [2, 419, 719]], []],
   [['hours_window', 3], ['hours_window', 2], ['hours_window', 3], ['hours_window', 2], ['daily_cap', 2],
    ['daily_cap', 3]]),
  ('boundary control 4', [15, [[5, 960, 1140]], []], []),
  ('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
  ('normal control 6', [16, [[1, 480, 960], [1, 420, 660]], [0, 3, 5, 6]], []),
  ('normal control 7', [17, [[2, 1080, 1260], [0, 419, 719]], [2, 4, 6]], []),
  ('normal control 8', [15, [[3, 419, 599], [4, 360, 420]], [3, 4, 5]],
   [['hours_window', 3], ['hours_window', 4]])],
 [('regression: daily total aggregation 1',
   [15, [[6, 360, 541], [1, 900, 960], [5, 480, 600], [1, 420, 660], [4, 900, 1020], [1, 1020, 1140]],
    [0, 1, 4, 5]],
   [['hours_window', 6], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [14, [[2, 360, 660], [6, 1080, 1380], [0, 1020, 1260], [2, 1080, 1200], [3, 420, 660], [5, 480, 661]],
    [0, 1, 2, 3, 5]],
   [['hours_window', 2], ['hours_window', 6], ['hours_window', 0], ['hours_window', 2], ['daily_cap', 0],
    ['daily_cap', 2], ['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
  ('partial repair guard 3',
   [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]]),
  ('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', [17, [[3, 900, 960], [3, 1020, 1260]], [0, 1, 2, 4, 5]], []),
  ('normal control 7', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], []),
  ('normal control 8', [16, [[3, 360, 541], [5, 1020, 1080], [0, 1080, 1260], [1, 420, 601]], []], [])],
 [('regression: daily total aggregation 1', [15, [[3, 960, 1141], [3, 1020, 1440]], [0, 2, 4, 5, 6]],
   [['hours_window', 3], ['hours_window', 3], ['daily_cap', 3]]),
  ('regression variant: daily total aggregation 2',
   [14, [[6, 900, 960], [0, 1080, 1440], [5, 419, 659], [0, 1020, 1080]], [0, 1, 3]],
   [['hours_window', 0], ['hours_window', 5], ['daily_cap', 0]]),
  ('partial repair guard 3',
   [15, [[1, 480, 660], [1, 1080, 1140], [1, 419, 479], [4, 1080, 1260]], [0, 1, 2, 5]],
   [['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('boundary control 4', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
  ('boundary control 5', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
   [['weekly_cap', -1]]),
  ('normal control 6', [14, [[2, 1080, 1380], [0, 420, 540], [6, 960, 1020]], [0, 1, 2, 3, 6]],
   [['hours_window', 2], ['daily_cap', 2]]),
  ('normal control 7',
   [15, [[5, 1080, 1140], [6, 419, 719], [3, 1080, 1200], [6, 419, 479], [4, 1020, 1200]], [0, 1, 2, 4]],
   [['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['hours_window', 4]]),
  ('normal control 8', [17, [[5, 900, 1081], [5, 1020, 1200], [0, 1080, 1261], [3, 960, 1080]], []], [])]]
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 fixtureActualExpectedOutcome
regression: daily total aggregation 1[][['daily_cap', 1]]Failed
regression variant: daily total aggregation 2[['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4]][['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]Failed
partial repair guard 3[['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 5]][['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1], ['daily_cap', 5], ['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', 1]]Passed
normal control 7[['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 3], ['daily_cap', 4]][['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]Failed
normal control 8[][]Passed

SHA-256 / 8d7bd1a27b17345218def06ecdf6bc5e6222c632e18ef891b4a0879d25ec97c5

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: daily total aggregation 1', [15, [[1, 900, 1000], [1, 1020, 1120]], [1]], [['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [15, [[0, 1020, 1200], [3, 1020, 1200], [1, 360, 540], [1, 420, 480], [4, 419, 599], [1, 900, 960]],
    [0, 1, 2, 3, 6]],
   [['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [15, [[1, 419, 599], [5, 1020, 1320], [1, 480, 720], [5, 420, 480], [2, 360, 600], [1, 1020, 1201]],
    [0, 3, 4, 5, 6]],
   [['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1],
    ['daily_cap', 5], ['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, 1200]], []], [['hours_window', 1]]),
  ('normal control 7',
   [15, [[3, 900, 1200], [1, 1020, 1201], [3, 900, 1081], [1, 419, 719], [4, 1080, 1261], [2, 960, 1020]],
    [0, 2, 3, 4, 5]],
   [['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1],
    ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]),
  ('normal control 8',
   [17, [[3, 1080, 1200], [2, 900, 1200], [6, 420, 480], [3, 1080, 1380], [2, 960, 1200]], [0, 2, 4]], [])],
 [('regression: daily total aggregation 1',
   [15, [[5, 1020, 1200], [5, 900, 960], [5, 360, 480], [5, 420, 600], [6, 360, 840], [0, 480, 660]], []],
   [['hours_window', 5], ['hours_window', 5], ['hours_window', 6], ['daily_cap', 5]]),
  ('regression variant: daily total aggregation 2',
   [15, [[6, 480, 660], [5, 420, 600], [1, 480, 660], [1, 360, 480]], [1, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('partial repair guard 3',
   [14, [[5, 480, 960], [0, 480, 960], [6, 960, 1200], [6, 960, 1260], [5, 900, 1020]], []],
   [['hours_window', 6], ['hours_window', 6], ['daily_cap', 5], ['daily_cap', 6]]),
  ('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',
   [15, [[0, 1020, 1080], [6, 1020, 1260], [3, 1020, 1320], [6, 480, 660], [2, 480, 960]], []],
   [['hours_window', 6], ['hours_window', 3]]),
  ('normal control 7',
   [17, [[1, 420, 601], [2, 1020, 1200], [0, 960, 1140], [0, 1080, 1320]], [0, 2, 3, 5, 6]], []),
  ('normal control 8', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], [])],
 [('regression: daily total aggregation 1', [14, [[1, 420, 601], [1, 960, 1260]], [0, 2, 3]],
   [['hours_window', 1], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [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]]),
  ('partial repair guard 3',
   [15, [[3, 419, 599], [3, 900, 1081], [2, 360, 660], [3, 360, 660], [2, 419, 719]], []],
   [['hours_window', 3], ['hours_window', 2], ['hours_window', 3], ['hours_window', 2], ['daily_cap', 2],
    ['daily_cap', 3]]),
  ('boundary control 4', [15, [[5, 960, 1140]], []], []),
  ('boundary control 5', [15, [[0, 900, 1080]], [0, 1, 2, 3, 4]], []),
  ('normal control 6', [16, [[1, 480, 960], [1, 420, 660]], [0, 3, 5, 6]], []),
  ('normal control 7', [17, [[2, 1080, 1260], [0, 419, 719]], [2, 4, 6]], []),
  ('normal control 8', [15, [[3, 419, 599], [4, 360, 420]], [3, 4, 5]],
   [['hours_window', 3], ['hours_window', 4]])],
 [('regression: daily total aggregation 1',
   [15, [[6, 360, 541], [1, 900, 960], [5, 480, 600], [1, 420, 660], [4, 900, 1020], [1, 1020, 1140]],
    [0, 1, 4, 5]],
   [['hours_window', 6], ['daily_cap', 1]]),
  ('regression variant: daily total aggregation 2',
   [14, [[2, 360, 660], [6, 1080, 1380], [0, 1020, 1260], [2, 1080, 1200], [3, 420, 660], [5, 480, 661]],
    [0, 1, 2, 3, 5]],
   [['hours_window', 2], ['hours_window', 6], ['hours_window', 0], ['hours_window', 2], ['daily_cap', 0],
    ['daily_cap', 2], ['daily_cap', 3], ['daily_cap', 5], ['weekly_cap', -1]]),
  ('partial repair guard 3',
   [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]]),
  ('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', [17, [[3, 900, 960], [3, 1020, 1260]], [0, 1, 2, 4, 5]], []),
  ('normal control 7', [16, [[4, 420, 540], [1, 1080, 1320]], [0, 1, 2, 3, 6]], []),
  ('normal control 8', [16, [[3, 360, 541], [5, 1020, 1080], [0, 1080, 1260], [1, 420, 601]], []], [])],
 [('regression: daily total aggregation 1', [15, [[3, 960, 1141], [3, 1020, 1440]], [0, 2, 4, 5, 6]],
   [['hours_window', 3], ['hours_window', 3], ['daily_cap', 3]]),
  ('regression variant: daily total aggregation 2',
   [14, [[6, 900, 960], [0, 1080, 1440], [5, 419, 659], [0, 1020, 1080]], [0, 1, 3]],
   [['hours_window', 0], ['hours_window', 5], ['daily_cap', 0]]),
  ('partial repair guard 3',
   [15, [[1, 480, 660], [1, 1080, 1140], [1, 419, 479], [4, 1080, 1260]], [0, 1, 2, 5]],
   [['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]),
  ('boundary control 4', [15, [[0, 900, 1081]], [0, 1, 2, 3, 4]], [['daily_cap', 0]]),
  ('boundary control 5', [14, [[5, 480, 960], [6, 480, 960], [0, 900, 1080], [2, 900, 1080]], [0, 2]],
   [['weekly_cap', -1]]),
  ('normal control 6', [14, [[2, 1080, 1380], [0, 420, 540], [6, 960, 1020]], [0, 1, 2, 3, 6]],
   [['hours_window', 2], ['daily_cap', 2]]),
  ('normal control 7',
   [15, [[5, 1080, 1140], [6, 419, 719], [3, 1080, 1200], [6, 419, 479], [4, 1020, 1200]], [0, 1, 2, 4]],
   [['hours_window', 6], ['hours_window', 3], ['hours_window', 6], ['hours_window', 4]]),
  ('normal control 8', [17, [[5, 900, 1081], [5, 1020, 1200], [0, 1080, 1261], [3, 960, 1080]], []], [])]]
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 fixtureActualExpectedOutcome
regression: daily total aggregation 1[['daily_cap', 1]][['daily_cap', 1]]Passed
regression variant: daily total aggregation 2[['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]][['hours_window', 0], ['hours_window', 3], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1]]Passed
partial repair guard 3[['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1], ['daily_cap', 5], ['weekly_cap', -1]][['hours_window', 1], ['hours_window', 5], ['hours_window', 2], ['hours_window', 1], ['daily_cap', 1], ['daily_cap', 5], ['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', 1]]Passed
normal control 7[['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]][['hours_window', 3], ['hours_window', 1], ['hours_window', 1], ['hours_window', 4], ['daily_cap', 1], ['daily_cap', 3], ['daily_cap', 4], ['weekly_cap', -1]]Passed
normal control 8[][]Passed

SHA-256 / 0df7c7bb3b28ce00a4d58b3d160767c7379f750bcdce79089922bdc5f8436538

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 2026-09-29T14:52:00.847177+00:00.

Case digest / 6489f201343193310a3897cba2974758512d9e6a58bf0c026a90a0d5dabbc6c4