FA-62391 / Tax bracket computation / Open access
A separate filer keeps the standard deduction while the spouse itemizes · case 01
Married-filing-separately returns claim a standard deduction the rules deny.
ROOT CAUSE
The mfs spouse-itemizes rule is not applied.
VERIFIED REPAIR
Set the standard deduction to zero when an mfs spouse itemizes.
Unsuccessful approach: Zeroing only the base amount still grants the additional age or blindness amounts.
Case contract
solve(status, gross, earned, itemized, conditions, dependent, spouse_itemizes): stipulated deduction rules. Base standard deduction: single 14600, mfj 29200, mfs 14600, hoh 21900 (other statuses 'ERR:status'). A dependent's base is min(base, max(1300, earned + 450)). Then add 1950 per age/blindness condition for single or hoh, 1550 per condition for married statuses. If status is mfs and the spouse itemizes, the standard deduction is 0. The deduction is the larger of standard and itemized; taxable = max(0, gross - deduction). Return [deduction, taxable].
Why this case matters
Tax computations hinge on which slice, threshold, ordering and rounding rule applies at each step; a misplaced boundary silently misstates liabilities.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(status, gross, earned, itemized, conditions, dependent, spouse_itemizes):
std = {'single': 14600, 'mfj': 29200, 'mfs': 14600, 'hoh': 21900}
if status not in std: return 'ERR:status'
extra = 1950 if status in ('single', 'hoh') else 1550
base = std[status]
if dependent: base = min(base, max(1300, earned + 450))
s = base + extra * conditions
pass
d = max(s, itemized)
return [d, max(0, gross - d)]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression mfs-spouse-itemizes 1', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('regression mfs-spouse-itemizes 2', ('mfs', 40000, 40000, 0, 0, False, True), [0, 40000]),
('partial repair guard 2', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('regression mfs-spouse-itemizes 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('partial repair guard 2', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])],
[('regression mfs-spouse-itemizes 1', ('mfs', 68513, 500, 0, 0, False, True), [0, 68513]),
('regression mfs-spouse-itemizes 2', ('mfs', 76535, 900, 0, 0, False, True), [0, 76535]),
('partial repair guard 1', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 2', ('mfs', 142325, 500, 0, 2, True, True), [0, 142325]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000]),
('control: bad status', ('widow', 1, 1, 0, 0, False, False), 'ERR:status'),
('control: dependent no earnings', ('single', 3000, 0, 0, 0, True, False), [1300, 1700]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400])],
[('regression mfs-spouse-itemizes 1', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('regression mfs-spouse-itemizes 2', ('mfs', 28199, 2000, 3000, 1, False, True), [3000, 25199]),
('partial repair guard 1', ('mfs', 97884, 0, 0, 2, True, True), [0, 97884]),
('partial repair guard 2', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 9614, 500, 0, 0, False, True), [0, 9614]),
('regression mfs-spouse-itemizes 2', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('partial repair guard 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])]]
for label, args, expected in cases[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 mfs-spouse-itemizes 1 | [17700, 22300] | [3000, 37000] | Failed |
| regression mfs-spouse-itemizes 2 | [14600, 25400] | [0, 40000] | Failed |
| partial repair guard 2 | [7538, 111128] | [0, 118666] | Failed |
| control: single standard | [14600, 35400] | [14600, 35400] | Passed |
| control: hoh with age | [23850, 6150] | [23850, 6150] | Passed |
| control: dependent | [2450, 2550] | [2450, 2550] | Passed |
| control: mfj below deduction | [32300, 0] | [32300, 0] | Passed |
SHA-256 / 9ed309285da1c082e05c96b5b38df0a5ee306ddd20c71171ee11904e287651dc
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(status, gross, earned, itemized, conditions, dependent, spouse_itemizes):
std = {'single': 14600, 'mfj': 29200, 'mfs': 14600, 'hoh': 21900}
if status not in std: return 'ERR:status'
extra = 1950 if status in ('single', 'hoh') else 1550
base = std[status]
if status == 'mfs' and spouse_itemizes: base = 0
if dependent: base = min(base, max(1300, earned + 450))
s = base + extra * conditions
pass
d = max(s, itemized)
return [d, max(0, gross - d)]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression mfs-spouse-itemizes 1', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('regression mfs-spouse-itemizes 2', ('mfs', 40000, 40000, 0, 0, False, True), [0, 40000]),
('partial repair guard 2', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('regression mfs-spouse-itemizes 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('partial repair guard 2', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])],
[('regression mfs-spouse-itemizes 1', ('mfs', 68513, 500, 0, 0, False, True), [0, 68513]),
('regression mfs-spouse-itemizes 2', ('mfs', 76535, 900, 0, 0, False, True), [0, 76535]),
('partial repair guard 1', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 2', ('mfs', 142325, 500, 0, 2, True, True), [0, 142325]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000]),
('control: bad status', ('widow', 1, 1, 0, 0, False, False), 'ERR:status'),
('control: dependent no earnings', ('single', 3000, 0, 0, 0, True, False), [1300, 1700]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400])],
[('regression mfs-spouse-itemizes 1', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('regression mfs-spouse-itemizes 2', ('mfs', 28199, 2000, 3000, 1, False, True), [3000, 25199]),
('partial repair guard 1', ('mfs', 97884, 0, 0, 2, True, True), [0, 97884]),
('partial repair guard 2', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 9614, 500, 0, 0, False, True), [0, 9614]),
('regression mfs-spouse-itemizes 2', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('partial repair guard 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])]]
for label, args, expected in cases[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 mfs-spouse-itemizes 1 | [3100, 36900] | [3000, 37000] | Failed |
| regression mfs-spouse-itemizes 2 | [0, 40000] | [0, 40000] | Passed |
| partial repair guard 2 | [1550, 117116] | [0, 118666] | Failed |
| control: single standard | [14600, 35400] | [14600, 35400] | Passed |
| control: hoh with age | [23850, 6150] | [23850, 6150] | Passed |
| control: dependent | [2450, 2550] | [2450, 2550] | Passed |
| control: mfj below deduction | [32300, 0] | [32300, 0] | Passed |
SHA-256 / a2da6498891c16eba8407bfc558ee41a3a9debeff0b4c947b2b35ea8a40b113f
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(status, gross, earned, itemized, conditions, dependent, spouse_itemizes):
std = {'single': 14600, 'mfj': 29200, 'mfs': 14600, 'hoh': 21900}
if status not in std: return 'ERR:status'
extra = 1950 if status in ('single', 'hoh') else 1550
base = std[status]
if dependent: base = min(base, max(1300, earned + 450))
s = base + extra * conditions
if status == 'mfs' and spouse_itemizes: s = 0
d = max(s, itemized)
return [d, max(0, gross - d)]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression mfs-spouse-itemizes 1', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('regression mfs-spouse-itemizes 2', ('mfs', 40000, 40000, 0, 0, False, True), [0, 40000]),
('partial repair guard 2', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('regression mfs-spouse-itemizes 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('partial repair guard 2', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])],
[('regression mfs-spouse-itemizes 1', ('mfs', 68513, 500, 0, 0, False, True), [0, 68513]),
('regression mfs-spouse-itemizes 2', ('mfs', 76535, 900, 0, 0, False, True), [0, 76535]),
('partial repair guard 1', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 2', ('mfs', 142325, 500, 0, 2, True, True), [0, 142325]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000]),
('control: bad status', ('widow', 1, 1, 0, 0, False, False), 'ERR:status'),
('control: dependent no earnings', ('single', 3000, 0, 0, 0, True, False), [1300, 1700]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400])],
[('regression mfs-spouse-itemizes 1', ('mfs', 60365, 500, 0, 1, True, True), [0, 60365]),
('regression mfs-spouse-itemizes 2', ('mfs', 28199, 2000, 3000, 1, False, True), [3000, 25199]),
('partial repair guard 1', ('mfs', 97884, 0, 0, 2, True, True), [0, 97884]),
('partial repair guard 2', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: single standard', ('single', 50000, 50000, 0, 0, False, False), [14600, 35400]),
('control: hoh with age', ('hoh', 30000, 30000, 0, 1, False, False), [23850, 6150]),
('control: dependent', ('single', 5000, 2000, 0, 0, True, False), [2450, 2550]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0])],
[('regression mfs-spouse-itemizes 1', ('mfs', 9614, 500, 0, 0, False, True), [0, 9614]),
('regression mfs-spouse-itemizes 2', ('mfs', 23561, 14000, 0, 2, False, True), [0, 23561]),
('partial repair guard 1', ('mfs', 118666, 5538, 0, 1, True, True), [0, 118666]),
('partial repair guard 2', ('mfs', 29019, 900, 0, 2, False, True), [0, 29019]),
('control: mfs spouse itemizes', ('mfs', 40000, 40000, 3000, 2, False, True), [3000, 37000]),
('control: mfj below deduction', ('mfj', 20000, 20000, 0, 2, False, False), [32300, 0]),
('control: high-earning dependent', ('single', 9000, 20000, 0, 1, True, False), [16550, 0]),
('control: itemizer', ('mfj', 120000, 120000, 35000, 0, False, False), [35000, 85000])]]
for label, args, expected in cases[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 mfs-spouse-itemizes 1 | [3000, 37000] | [3000, 37000] | Passed |
| regression mfs-spouse-itemizes 2 | [0, 40000] | [0, 40000] | Passed |
| partial repair guard 2 | [0, 118666] | [0, 118666] | Passed |
| control: single standard | [14600, 35400] | [14600, 35400] | Passed |
| control: hoh with age | [23850, 6150] | [23850, 6150] | Passed |
| control: dependent | [2450, 2550] | [2450, 2550] | Passed |
| control: mfj below deduction | [32300, 0] | [32300, 0] | Passed |
SHA-256 / 5db5ebca633df5f8ab311ef4700176225391c590450cbf51be9d7ef251f086e5
Verification & scope
A deterministic, bounded teaching model with a stipulated toy contract; it makes no claim of conformance to any real regulation, standard, or institution's rules. 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 2026-09-29T14:47:04.151678+00:00.
Case digest / 2aaf59797add0d7927cd26cad028826f3ce6d2699657c2292e84c33b4910ca31