FA-58911 / Payroll withholding rules / Open access
W-4 step adjustment withholding: other income annualization · case 01
Employees reporting other income are withheld as if that income recurred every paycheck.
ROOT CAUSE
Step 4(a) other income, already an annual figure, is multiplied by the number of pay periods.
VERIFIED REPAIR
Restore the contract rule at the other income annualization step: use `annual = x['wage'] * p + x['other_income']`.
Unsuccessful approach: The attempt divides the annual other income by periods before annualizing, so only a fraction of it is counted.
Case contract
Input {wage, periods, status single|mfj|hoh, step2, credits, other_income, deductions, extra}; annual amounts in cents except wage and extra (per period). Annual = wage*periods + other_income. Deduction = base standard (single 8,600, mfj 12,900, hoh 8,600 dollars; halved when step2) + itemized deductions (never halved). Thresholds 7,000/30,000/90,000 dollars at 10/12/22% scaled by status unit (single 2, mfj 4, hoh 3)/2, or /4 when step2. Tentative per-period = annual tax/periods half-up; credits/periods half-up is subtracted, floored at 0, then extra is added.
Why this case matters
Modern W-4 withholding combines annual adjustments with per-period ones, and the order of flooring and adding extra withholding matters.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
p = x['periods']
annual = (x['wage'] + x['other_income']) * p
base_std = {'single': 860000, 'mfj': 1290000, 'hoh': 860000}[x['status']]
ded = (base_std // 2 if x['step2'] else base_std) + x['deductions']
taxable = max(0, annual - ded)
unit = {'single': 2, 'mfj': 4, 'hoh': 3}[x['status']]
div = 4 if x['step2'] else 2
bounds = [700000 * unit // div, 3000000 * unit // div, 9000000 * unit // div]
rates = [10, 12, 22]
tax = 0
for i, lo in enumerate(bounds):
hi = bounds[i + 1] if i + 1 < len(bounds) else taxable
if taxable > lo:
tax += (min(taxable, hi) - lo) * rates[i]
tentative = (tax * 2 + 100 * p) // (200 * p)
credit_pp = (x['credits'] * 2 + p) // (2 * p)
wh = max(0, tentative - credit_pp) + x['extra']
return [tentative, wh]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'wage': 4942, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 1831505, 'deductions': 0, 'extra': 8860}, [2757, 8860]), ('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('partial-repair probe', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 111690, 'periods': 26, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [823, 823]), ('normal control', {'wage': 67447, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 1041418, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [156854, 159354]), ('normal control', {'wage': 245742, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19772, 22272])], [('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 196398, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [6640, 6640]), ('normal control', {'wage': 64669, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 232685, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 0, 'deductions': 479252, 'extra': 0}, [18839, 14993]), ('normal control', {'wage': 322003, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19207, 21707])], [('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('partial-repair probe', {'wage': 170108, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 200000, 'other_income': 167672, 'deductions': 0, 'extra': 0}, [12373, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 285367, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 1182238, 'extra': 2500}, [41104, 43604]), ('normal control', {'wage': 179669, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [17076, 17076]), ('normal control', {'wage': 124748, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [7302, 7302]), ('normal control', {'wage': 90292, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [7968, 10468])], [('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 244499, 'periods': 26, 'status': 'hoh', 'step2': False, 'credits': 305778, 'other_income': 170107, 'deductions': 0, 'extra': 0}, [18656, 6895]), ('partial-repair probe', {'wage': 290758, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 1100573, 'deductions': 944056, 'extra': 0}, [26644, 26644]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 250357, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [31632, 34132]), ('normal control', {'wage': 142479, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 551126, 'other_income': 0, 'deductions': 0, 'extra': 3806}, [14670, 7877]), ('normal control', {'wage': 251742, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 392790, 'extra': 0}, [23568, 23568]), ('normal control', {'wage': 76761, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [4003, 2500])], [('regression', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 606158, 'periods': 26, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 1548001, 'deductions': 0, 'extra': 0}, [113103, 113103]), ('partial-repair probe', {'wage': 667888, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 200000, 'other_income': 923171, 'deductions': 893525, 'extra': 2500}, [74949, 69116]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 451331, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [54220, 54220]), ('normal control', {'wage': 37554, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 695042, 'extra': 0}, [0, 0]), ('normal control', {'wage': 80276, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 10576}, [5149, 10576]), ('normal control', {'wage': 23105, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500])]]
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 | [302418, 277945] | [2757, 8860] | Failed |
| regression 1 | [348543, 311971] | [5927, 0] | Failed |
| partial-repair probe 2 | [86474, 53141] | [59948, 26615] | Failed |
| partial-repair probe 3 | [329807, 313140] | [4460, 0] | Failed |
| boundary control 4 | [0, 5000] | [0, 5000] | Passed |
| normal control 5 | [823, 823] | [823, 823] | Passed |
| normal control 6 | [0, 2500] | [0, 2500] | Passed |
| normal control 7 | [156854, 159354] | [156854, 159354] | Passed |
| normal control 8 | [19772, 22272] | [19772, 22272] | Passed |
SHA-256 / 39d6afa71d5cb9fe0e7f0be5403bed8b15bb8a4f30c29d04fb0847f060b9774b
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
p = x['periods']
annual = x['wage'] * p + x['other_income'] // p
base_std = {'single': 860000, 'mfj': 1290000, 'hoh': 860000}[x['status']]
ded = (base_std // 2 if x['step2'] else base_std) + x['deductions']
taxable = max(0, annual - ded)
unit = {'single': 2, 'mfj': 4, 'hoh': 3}[x['status']]
div = 4 if x['step2'] else 2
bounds = [700000 * unit // div, 3000000 * unit // div, 9000000 * unit // div]
rates = [10, 12, 22]
tax = 0
for i, lo in enumerate(bounds):
hi = bounds[i + 1] if i + 1 < len(bounds) else taxable
if taxable > lo:
tax += (min(taxable, hi) - lo) * rates[i]
tentative = (tax * 2 + 100 * p) // (200 * p)
credit_pp = (x['credits'] * 2 + p) // (2 * p)
wh = max(0, tentative - credit_pp) + x['extra']
return [tentative, wh]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'wage': 4942, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 1831505, 'deductions': 0, 'extra': 8860}, [2757, 8860]), ('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('partial-repair probe', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 111690, 'periods': 26, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [823, 823]), ('normal control', {'wage': 67447, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 1041418, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [156854, 159354]), ('normal control', {'wage': 245742, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19772, 22272])], [('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 196398, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [6640, 6640]), ('normal control', {'wage': 64669, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 232685, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 0, 'deductions': 479252, 'extra': 0}, [18839, 14993]), ('normal control', {'wage': 322003, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19207, 21707])], [('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('partial-repair probe', {'wage': 170108, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 200000, 'other_income': 167672, 'deductions': 0, 'extra': 0}, [12373, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 285367, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 1182238, 'extra': 2500}, [41104, 43604]), ('normal control', {'wage': 179669, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [17076, 17076]), ('normal control', {'wage': 124748, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [7302, 7302]), ('normal control', {'wage': 90292, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [7968, 10468])], [('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 244499, 'periods': 26, 'status': 'hoh', 'step2': False, 'credits': 305778, 'other_income': 170107, 'deductions': 0, 'extra': 0}, [18656, 6895]), ('partial-repair probe', {'wage': 290758, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 1100573, 'deductions': 944056, 'extra': 0}, [26644, 26644]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 250357, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [31632, 34132]), ('normal control', {'wage': 142479, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 551126, 'other_income': 0, 'deductions': 0, 'extra': 3806}, [14670, 7877]), ('normal control', {'wage': 251742, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 392790, 'extra': 0}, [23568, 23568]), ('normal control', {'wage': 76761, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [4003, 2500])], [('regression', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 606158, 'periods': 26, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 1548001, 'deductions': 0, 'extra': 0}, [113103, 113103]), ('partial-repair probe', {'wage': 667888, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 200000, 'other_income': 923171, 'deductions': 893525, 'extra': 2500}, [74949, 69116]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 451331, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [54220, 54220]), ('normal control', {'wage': 37554, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 695042, 'extra': 0}, [0, 0]), ('normal control', {'wage': 80276, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 10576}, [5149, 10576]), ('normal control', {'wage': 23105, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500])]]
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 | [0, 8860] | [2757, 8860] | Failed |
| regression 1 | [0, 0] | [5927, 0] | Failed |
| partial-repair probe 2 | [57737, 24404] | [59948, 26615] | Failed |
| partial-repair probe 3 | [0, 0] | [4460, 0] | Failed |
| boundary control 4 | [0, 5000] | [0, 5000] | Passed |
| normal control 5 | [823, 823] | [823, 823] | Passed |
| normal control 6 | [0, 2500] | [0, 2500] | Passed |
| normal control 7 | [156854, 159354] | [156854, 159354] | Passed |
| normal control 8 | [19772, 22272] | [19772, 22272] | Passed |
SHA-256 / 56890c46fc9bda6bd1e1c2b6fe2a55e6470d0351fccee2873f94d97112c6f921
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
p = x['periods']
annual = x['wage'] * p + x['other_income']
base_std = {'single': 860000, 'mfj': 1290000, 'hoh': 860000}[x['status']]
ded = (base_std // 2 if x['step2'] else base_std) + x['deductions']
taxable = max(0, annual - ded)
unit = {'single': 2, 'mfj': 4, 'hoh': 3}[x['status']]
div = 4 if x['step2'] else 2
bounds = [700000 * unit // div, 3000000 * unit // div, 9000000 * unit // div]
rates = [10, 12, 22]
tax = 0
for i, lo in enumerate(bounds):
hi = bounds[i + 1] if i + 1 < len(bounds) else taxable
if taxable > lo:
tax += (min(taxable, hi) - lo) * rates[i]
tentative = (tax * 2 + 100 * p) // (200 * p)
credit_pp = (x['credits'] * 2 + p) // (2 * p)
wh = max(0, tentative - credit_pp) + x['extra']
return [tentative, wh]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression', {'wage': 4942, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 1831505, 'deductions': 0, 'extra': 8860}, [2757, 8860]), ('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('partial-repair probe', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 111690, 'periods': 26, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [823, 823]), ('normal control', {'wage': 67447, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 1041418, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [156854, 159354]), ('normal control', {'wage': 245742, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19772, 22272])], [('regression', {'wage': 69636, 'periods': 24, 'status': 'hoh', 'step2': True, 'credits': 877725, 'other_income': 1721162, 'deductions': 1014955, 'extra': 0}, [5927, 0]), ('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('partial-repair probe', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 196398, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [6640, 6640]), ('normal control', {'wage': 64669, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500]), ('normal control', {'wage': 232685, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 0, 'deductions': 479252, 'extra': 0}, [18839, 14993]), ('normal control', {'wage': 322003, 'periods': 12, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [19207, 21707])], [('regression', {'wage': 492438, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 400000, 'other_income': 131536, 'deductions': 0, 'extra': 0}, [59948, 26615]), ('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('partial-repair probe', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('partial-repair probe', {'wage': 170108, 'periods': 12, 'status': 'single', 'step2': True, 'credits': 200000, 'other_income': 167672, 'deductions': 0, 'extra': 0}, [12373, 0]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 285367, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 1182238, 'extra': 2500}, [41104, 43604]), ('normal control', {'wage': 179669, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [17076, 17076]), ('normal control', {'wage': 124748, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [7302, 7302]), ('normal control', {'wage': 90292, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [7968, 10468])], [('regression', {'wage': 79014, 'periods': 24, 'status': 'mfj', 'step2': False, 'credits': 400000, 'other_income': 1864011, 'deductions': 0, 'extra': 0}, [4460, 0]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 244499, 'periods': 26, 'status': 'hoh', 'step2': False, 'credits': 305778, 'other_income': 170107, 'deductions': 0, 'extra': 0}, [18656, 6895]), ('partial-repair probe', {'wage': 290758, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 1100573, 'deductions': 944056, 'extra': 0}, [26644, 26644]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 250357, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [31632, 34132]), ('normal control', {'wage': 142479, 'periods': 52, 'status': 'hoh', 'step2': True, 'credits': 551126, 'other_income': 0, 'deductions': 0, 'extra': 3806}, [14670, 7877]), ('normal control', {'wage': 251742, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 392790, 'extra': 0}, [23568, 23568]), ('normal control', {'wage': 76761, 'periods': 52, 'status': 'hoh', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [4003, 2500])], [('regression', {'wage': 37313, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 117737, 'other_income': 1320234, 'deductions': 0, 'extra': 5664}, [1097, 5664]), ('regression', {'wage': 93316, 'periods': 12, 'status': 'mfj', 'step2': False, 'credits': 200000, 'other_income': 1111591, 'deductions': 0, 'extra': 1563}, [0, 1563]), ('partial-repair probe', {'wage': 606158, 'periods': 26, 'status': 'hoh', 'step2': True, 'credits': 0, 'other_income': 1548001, 'deductions': 0, 'extra': 0}, [113103, 113103]), ('partial-repair probe', {'wage': 667888, 'periods': 24, 'status': 'hoh', 'step2': False, 'credits': 200000, 'other_income': 923171, 'deductions': 893525, 'extra': 2500}, [74949, 69116]), ('boundary control', {'wage': 0, 'periods': 26, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 5000}, [0, 5000]), ('normal control', {'wage': 451331, 'periods': 52, 'status': 'mfj', 'step2': False, 'credits': 0, 'other_income': 0, 'deductions': 0, 'extra': 0}, [54220, 54220]), ('normal control', {'wage': 37554, 'periods': 26, 'status': 'mfj', 'step2': True, 'credits': 0, 'other_income': 0, 'deductions': 695042, 'extra': 0}, [0, 0]), ('normal control', {'wage': 80276, 'periods': 52, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 10576}, [5149, 10576]), ('normal control', {'wage': 23105, 'periods': 24, 'status': 'single', 'step2': False, 'credits': 400000, 'other_income': 0, 'deductions': 0, 'extra': 2500}, [0, 2500])]]
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 | [2757, 8860] | [2757, 8860] | Passed |
| regression 1 | [5927, 0] | [5927, 0] | Passed |
| partial-repair probe 2 | [59948, 26615] | [59948, 26615] | Passed |
| partial-repair probe 3 | [4460, 0] | [4460, 0] | Passed |
| boundary control 4 | [0, 5000] | [0, 5000] | Passed |
| normal control 5 | [823, 823] | [823, 823] | Passed |
| normal control 6 | [0, 2500] | [0, 2500] | Passed |
| normal control 7 | [156854, 159354] | [156854, 159354] | Passed |
| normal control 8 | [19772, 22272] | [19772, 22272] | Passed |
SHA-256 / f53ad341cac637bd6c7c4d2b2fb9e5690c41011af0d6d540093caaf422f2afb1
Verification & scope
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.
Observations recorded using Python 3.12.14 at 2026-09-29T14:46:31.179842+00:00.
Case digest / 3b2d45264f6d433f136dd01e0b7dc851553683bac5f3eb554c8b3a468ed29ff1