{"abstract":"Young workers in states with their own minimum wage are paid the youth rate.","category":"Payroll withholding rules","checks":8,"contract":"Input {federal, state|None, local|None, age, days_employed, hours, paid}. Applicable rate is the highest of the defined federal, state and local minimums. A youth rate of 4.25 may replace it when age < 20, days_employed <= 90 and neither a state nor local minimum is defined. Return [rate, max(0, hours*rate - paid)].","evaluation_group":"w2-payroll-withholding-minimum-wage-jurisdiction","failed_approach":"The attempt checks for a state minimum but still applies the youth rate under local ordinances.","family":"w2-payroll-withholding-minimum-wage-jurisdiction-youth-rate-preemption","id":"FA-59176","implementations":{"attempt":{"sha256":"ed39766e5c42fd6ba4104dc4fc30241c30ad21c4c236e4169d29d23f89093080","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    rates = [x['federal']] + [r for r in (x['state'], x['local']) if r is not None]\n    applicable = max(rates)\n    if x['age'] < 20 and x['days_employed'] <= 90 and x['state'] is None:\n        applicable = min(applicable, 425)\n    return [applicable, max(0, x['hours'] * applicable - x['paid'])]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': None, 'age': 17, 'days_employed': 10, 'hours': 44, 'paid': 52557}, [1500, 13443]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 21, 'days_employed': 10, 'hours': 36, 'paid': 32014}, [900, 386]), ('normal control', {'federal': 725, 'state': 1500, 'local': 900, 'age': 19, 'days_employed': 200, 'hours': 32, 'paid': 60214}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 19, 'days_employed': 200, 'hours': 49, 'paid': 66535}, [725, 0]), ('normal control', {'federal': 725, 'state': 700, 'local': 1400, 'age': 20, 'days_employed': 119, 'hours': 50, 'paid': 49362}, [1400, 20638])], [('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('regression', {'federal': 725, 'state': 700, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 42, 'paid': 43650}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 17, 'days_employed': 200, 'hours': 12, 'paid': 62529}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 91, 'hours': 13, 'paid': 52409}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 1700, 'age': 21, 'days_employed': 200, 'hours': 31, 'paid': 26649}, [1700, 26051]), ('normal control', {'federal': 725, 'state': 700, 'local': None, 'age': 35, 'days_employed': 200, 'hours': 25, 'paid': 55516}, [725, 0])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 19, 'days_employed': 90, 'hours': 35, 'paid': 10142}, [1500, 42358]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 89, 'hours': 9, 'paid': 34655}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 91, 'hours': 3, 'paid': 73893}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 44, 'paid': 29457}, [900, 10143]), ('normal control', {'federal': 725, 'state': 800, 'local': 1400, 'age': 21, 'days_employed': 89, 'hours': 42, 'paid': 70854}, [1400, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 27, 'paid': 8188}, [900, 16112])], [('regression', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 17, 'paid': 63085}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 37, 'paid': 49772}, [1400, 2028]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 200, 'hours': 2, 'paid': 39319}, [900, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 21, 'days_employed': 100, 'hours': 38, 'paid': 59758}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 35, 'days_employed': 91, 'hours': 1, 'paid': 31574}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 89, 'hours': 20, 'paid': 19880}, [1500, 10120])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('regression', {'federal': 725, 'state': 800, 'local': 1700, 'age': 19, 'days_employed': 10, 'hours': 35, 'paid': 45995}, [1700, 13505]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 19, 'days_employed': 89, 'hours': 11, 'paid': 62799}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 20, 'days_employed': 89, 'hours': 13, 'paid': 20235}, [1500, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 1700, 'age': 17, 'days_employed': 119, 'hours': 36, 'paid': 42057}, [1700, 19143]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 100, 'hours': 21, 'paid': 76399}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 20, 'days_employed': 91, 'hours': 50, 'paid': 25834}, [725, 10416])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"e07c60244cd936ca89c900e64df8ca6f7a932012fe54d5d65d2d858ba2450c91","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    rates = [x['federal']] + [r for r in (x['state'], x['local']) if r is not None]\n    applicable = max(rates)\n    if x['age'] < 20 and x['days_employed'] <= 90 :\n        applicable = min(applicable, 425)\n    return [applicable, max(0, x['hours'] * applicable - x['paid'])]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': None, 'age': 17, 'days_employed': 10, 'hours': 44, 'paid': 52557}, [1500, 13443]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 21, 'days_employed': 10, 'hours': 36, 'paid': 32014}, [900, 386]), ('normal control', {'federal': 725, 'state': 1500, 'local': 900, 'age': 19, 'days_employed': 200, 'hours': 32, 'paid': 60214}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 19, 'days_employed': 200, 'hours': 49, 'paid': 66535}, [725, 0]), ('normal control', {'federal': 725, 'state': 700, 'local': 1400, 'age': 20, 'days_employed': 119, 'hours': 50, 'paid': 49362}, [1400, 20638])], [('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('regression', {'federal': 725, 'state': 700, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 42, 'paid': 43650}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 17, 'days_employed': 200, 'hours': 12, 'paid': 62529}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 91, 'hours': 13, 'paid': 52409}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 1700, 'age': 21, 'days_employed': 200, 'hours': 31, 'paid': 26649}, [1700, 26051]), ('normal control', {'federal': 725, 'state': 700, 'local': None, 'age': 35, 'days_employed': 200, 'hours': 25, 'paid': 55516}, [725, 0])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 19, 'days_employed': 90, 'hours': 35, 'paid': 10142}, [1500, 42358]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 89, 'hours': 9, 'paid': 34655}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 91, 'hours': 3, 'paid': 73893}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 44, 'paid': 29457}, [900, 10143]), ('normal control', {'federal': 725, 'state': 800, 'local': 1400, 'age': 21, 'days_employed': 89, 'hours': 42, 'paid': 70854}, [1400, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 27, 'paid': 8188}, [900, 16112])], [('regression', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 17, 'paid': 63085}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 37, 'paid': 49772}, [1400, 2028]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 200, 'hours': 2, 'paid': 39319}, [900, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 21, 'days_employed': 100, 'hours': 38, 'paid': 59758}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 35, 'days_employed': 91, 'hours': 1, 'paid': 31574}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 89, 'hours': 20, 'paid': 19880}, [1500, 10120])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('regression', {'federal': 725, 'state': 800, 'local': 1700, 'age': 19, 'days_employed': 10, 'hours': 35, 'paid': 45995}, [1700, 13505]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 19, 'days_employed': 89, 'hours': 11, 'paid': 62799}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 20, 'days_employed': 89, 'hours': 13, 'paid': 20235}, [1500, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 1700, 'age': 17, 'days_employed': 119, 'hours': 36, 'paid': 42057}, [1700, 19143]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 100, 'hours': 21, 'paid': 76399}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 20, 'days_employed': 91, 'hours': 50, 'paid': 25834}, [725, 10416])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"904a2c75bf665fef7b93e1aacd1f72e1f0964ba79bf8ada3fe5d91cc6988e967","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    rates = [x['federal']] + [r for r in (x['state'], x['local']) if r is not None]\n    applicable = max(rates)\n    if x['age'] < 20 and x['days_employed'] <= 90 and x['state'] is None and x['local'] is None:\n        applicable = min(applicable, 425)\n    return [applicable, max(0, x['hours'] * applicable - x['paid'])]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': None, 'age': 17, 'days_employed': 10, 'hours': 44, 'paid': 52557}, [1500, 13443]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 21, 'days_employed': 10, 'hours': 36, 'paid': 32014}, [900, 386]), ('normal control', {'federal': 725, 'state': 1500, 'local': 900, 'age': 19, 'days_employed': 200, 'hours': 32, 'paid': 60214}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 19, 'days_employed': 200, 'hours': 49, 'paid': 66535}, [725, 0]), ('normal control', {'federal': 725, 'state': 700, 'local': 1400, 'age': 20, 'days_employed': 119, 'hours': 50, 'paid': 49362}, [1400, 20638])], [('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 90, 'hours': 18, 'paid': 17771}, [1700, 12829]), ('regression', {'federal': 725, 'state': 700, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 42, 'paid': 43650}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 17, 'days_employed': 200, 'hours': 12, 'paid': 62529}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 91, 'hours': 13, 'paid': 52409}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 1700, 'age': 21, 'days_employed': 200, 'hours': 31, 'paid': 26649}, [1700, 26051]), ('normal control', {'federal': 725, 'state': 700, 'local': None, 'age': 35, 'days_employed': 200, 'hours': 25, 'paid': 55516}, [725, 0])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 90, 'hours': 1, 'paid': 51150}, [900, 0]), ('regression', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 19, 'days_employed': 90, 'hours': 35, 'paid': 10142}, [1500, 42358]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 17, 'days_employed': 89, 'hours': 9, 'paid': 34655}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 91, 'hours': 3, 'paid': 73893}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 44, 'paid': 29457}, [900, 10143]), ('normal control', {'federal': 725, 'state': 800, 'local': 1400, 'age': 21, 'days_employed': 89, 'hours': 42, 'paid': 70854}, [1400, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 900, 'age': 35, 'days_employed': 10, 'hours': 27, 'paid': 8188}, [900, 16112])], [('regression', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 89, 'hours': 27, 'paid': 71203}, [1400, 0]), ('regression', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 17, 'paid': 63085}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 17, 'days_employed': 90, 'hours': 37, 'paid': 49772}, [1400, 2028]), ('normal control', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 200, 'hours': 2, 'paid': 39319}, [900, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 21, 'days_employed': 100, 'hours': 38, 'paid': 59758}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 35, 'days_employed': 91, 'hours': 1, 'paid': 31574}, [1500, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 21, 'days_employed': 89, 'hours': 20, 'paid': 19880}, [1500, 10120])], [('regression', {'federal': 725, 'state': None, 'local': 900, 'age': 17, 'days_employed': 10, 'hours': 4, 'paid': 8906}, [900, 0]), ('regression', {'federal': 725, 'state': 800, 'local': 1700, 'age': 19, 'days_employed': 10, 'hours': 35, 'paid': 45995}, [1700, 13505]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1400, 'age': 19, 'days_employed': 89, 'hours': 11, 'paid': 62799}, [1400, 0]), ('partial-repair probe', {'federal': 725, 'state': None, 'local': 1700, 'age': 19, 'days_employed': 90, 'hours': 1, 'paid': 33812}, [1700, 0]), ('normal control', {'federal': 725, 'state': 1500, 'local': 1400, 'age': 20, 'days_employed': 89, 'hours': 13, 'paid': 20235}, [1500, 0]), ('normal control', {'federal': 725, 'state': 800, 'local': 1700, 'age': 17, 'days_employed': 119, 'hours': 36, 'paid': 42057}, [1700, 19143]), ('normal control', {'federal': 725, 'state': 1500, 'local': None, 'age': 19, 'days_employed': 100, 'hours': 21, 'paid': 76399}, [1500, 0]), ('normal control', {'federal': 725, 'state': None, 'local': None, 'age': 20, 'days_employed': 91, 'hours': 50, 'paid': 25834}, [725, 10416])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, i), solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic teaching model of a stipulated payroll rule with toy thresholds and rates. It makes no claim of conformance to any tax authority, statute or jurisdiction and is not payroll 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.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-payroll-withholding-minimum-wage-jurisdiction-youth-rate-preemption","generated_at":"2026-09-29T14:46:33.805182+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Payroll must pay the most protective minimum wage, and the youth rate exception is narrow.","repair":"Restore the contract rule at the youth rate preemption step: use `and x['state'] is None and x['local'] is None`.","root_cause":"The youth rate is applied without checking whether a state or local minimum exists.","sha256":"3f18a8513ccdd7eb2c54c40b8a9f0f0652ab2d43063dde234c77dae312029c21","title":"Applicable minimum wage and youth rate: youth rate preemption · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":44.651,"exit_code":1,"observations":[{"actual":[425,0],"check":"regression 0","expected":[1700,0],"passed":false},{"actual":[1500,13443],"check":"regression 1","expected":[1500,13443],"passed":true},{"actual":[425,0],"check":"partial-repair probe 2","expected":[1700,12829],"passed":false},{"actual":[425,0],"check":"partial-repair probe 3","expected":[900,0],"passed":false},{"actual":[900,386],"check":"normal control 4","expected":[900,386],"passed":true},{"actual":[1500,0],"check":"normal control 5","expected":[1500,0],"passed":true},{"actual":[725,0],"check":"normal control 6","expected":[725,0],"passed":true},{"actual":[1400,20638],"check":"normal control 7","expected":[1400,20638],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [425, 0], \"expected\": [1700, 0], \"passed\": 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\"normal control 7\", \"actual\": [1400, 20638], \"expected\": [1400, 20638], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}