FAILURE MAP
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FA-62821 / Tax bracket computation / Open access

Joint filers use the single phase-out threshold · case 01

Married couples start losing the credit at 200000.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The threshold table ignores filing status.

VERIFIED REPAIR

Use 400000 for joint filers.

Unsuccessful approach: Using a 300000 joint threshold still starts the phase-out too early.

Case contract

solve(kids, others, magi, status, tax, earned): stipulated child credit, whole dollars. Credit = 2000 per child + 500 per other dependent, reduced by 50 for each 1000 or fraction thereof of MAGI above the threshold (single 200000, mfj 400000), floored at 0. The credit first offsets tax (used = min(credit, tax)); the refundable portion is min(credit - used, 1700 per child, 15% of earned income above 2500 rounded down, floored at 0). Return [credit, used, refundable].

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(kids, others, magi, status, tax, earned):
    thr = 200000
    credit = 2000 * kids + 500 * others
    if magi > thr: credit = max(0, credit - 50 * (-(-(magi - thr) // 1000)))
    used = min(credit, tax)
    refundable = min(credit - used, 1700 * kids, max(0, (earned - 2500) * 15 // 100))
    return [credit, used, refundable]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression joint-threshold 1', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('regression joint-threshold 2', (2, 0, 350000, 'mfj', 1000, 350000), [4000, 1000, 3000]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 450000, 'mfj', 10000, 30481), [1500, 1500, 0]),
  ('regression joint-threshold 2', (0, 2, 400001, 'mfj', 500, 3000), [950, 500, 0]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0])],
 [('regression joint-threshold 1', (3, 0, 200001, 'mfj', 10000, 24871), [6000, 6000, 0]),
  ('regression joint-threshold 2', (3, 0, 200001, 'mfj', 10000, 30000), [6000, 6000, 0]),
  ('partial repair guard 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('partial repair guard 2', (1, 2, 450000, 'mfj', 0, 10000), [500, 0, 500]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125])],
 [('regression joint-threshold 1', (1, 0, 201000, 'mfj', 0, 2000), [2000, 0, 0]),
  ('regression joint-threshold 2', (2, 1, 275424, 'mfj', 0, 10000), [4500, 0, 1125]),
  ('partial repair guard 1', (3, 2, 450000, 'mfj', 500, 0), [4500, 500, 0]),
  ('partial repair guard 2', (1, 0, 400001, 'mfj', 5000, 42362), [1950, 1950, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('regression joint-threshold 2', (1, 0, 201000, 'mfj', 5000, 10000), [2000, 2000, 0]),
  ('partial repair guard 1', (1, 0, 400001, 'mfj', 0, 30000), [1950, 0, 1700]),
  ('partial repair guard 2', (3, 2, 450000, 'mfj', 5000, 30000), [4500, 4500, 0]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0])]]
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 fixtureActualExpectedOutcome
regression joint-threshold 1[0, 0, 0][6450, 1000, 5100]Failed
regression joint-threshold 2[0, 0, 0][4000, 1000, 3000]Failed
control: refund limited by child cap[4000, 1000, 3000][4000, 1000, 3000]Passed
control: fraction thereof[4400, 4400, 0][4400, 4400, 0]Passed
control: earned limit[2000, 0, 1125][2000, 0, 1125]Passed
control: fully phased[0, 0, 0][0, 0, 0]Passed

SHA-256 / c2be88dc59f03520a2d6ffa911f3e512f7bc550d51b4fdc8c37e10907f2ea939

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(kids, others, magi, status, tax, earned):
    thr = {'single': 200000, 'mfj': 300000}[status]
    credit = 2000 * kids + 500 * others
    if magi > thr: credit = max(0, credit - 50 * (-(-(magi - thr) // 1000)))
    used = min(credit, tax)
    refundable = min(credit - used, 1700 * kids, max(0, (earned - 2500) * 15 // 100))
    return [credit, used, refundable]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression joint-threshold 1', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('regression joint-threshold 2', (2, 0, 350000, 'mfj', 1000, 350000), [4000, 1000, 3000]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 450000, 'mfj', 10000, 30481), [1500, 1500, 0]),
  ('regression joint-threshold 2', (0, 2, 400001, 'mfj', 500, 3000), [950, 500, 0]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0])],
 [('regression joint-threshold 1', (3, 0, 200001, 'mfj', 10000, 24871), [6000, 6000, 0]),
  ('regression joint-threshold 2', (3, 0, 200001, 'mfj', 10000, 30000), [6000, 6000, 0]),
  ('partial repair guard 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('partial repair guard 2', (1, 2, 450000, 'mfj', 0, 10000), [500, 0, 500]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125])],
 [('regression joint-threshold 1', (1, 0, 201000, 'mfj', 0, 2000), [2000, 0, 0]),
  ('regression joint-threshold 2', (2, 1, 275424, 'mfj', 0, 10000), [4500, 0, 1125]),
  ('partial repair guard 1', (3, 2, 450000, 'mfj', 500, 0), [4500, 500, 0]),
  ('partial repair guard 2', (1, 0, 400001, 'mfj', 5000, 42362), [1950, 1950, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('regression joint-threshold 2', (1, 0, 201000, 'mfj', 5000, 10000), [2000, 2000, 0]),
  ('partial repair guard 1', (1, 0, 400001, 'mfj', 0, 30000), [1950, 0, 1700]),
  ('partial repair guard 2', (3, 2, 450000, 'mfj', 5000, 30000), [4500, 4500, 0]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0])]]
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 fixtureActualExpectedOutcome
regression joint-threshold 1[1450, 1000, 450][6450, 1000, 5100]Failed
regression joint-threshold 2[1500, 1000, 500][4000, 1000, 3000]Failed
control: refund limited by child cap[4000, 1000, 3000][4000, 1000, 3000]Passed
control: fraction thereof[4400, 4400, 0][4400, 4400, 0]Passed
control: earned limit[2000, 0, 1125][2000, 0, 1125]Passed
control: fully phased[0, 0, 0][0, 0, 0]Passed

SHA-256 / ea28eeb40a5a5323efa51206779d1d6d29df4b12968be9caa47a6ff305cf8259

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(kids, others, magi, status, tax, earned):
    thr = {'single': 200000, 'mfj': 400000}[status]
    credit = 2000 * kids + 500 * others
    if magi > thr: credit = max(0, credit - 50 * (-(-(magi - thr) // 1000)))
    used = min(credit, tax)
    refundable = min(credit - used, 1700 * kids, max(0, (earned - 2500) * 15 // 100))
    return [credit, used, refundable]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression joint-threshold 1', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('regression joint-threshold 2', (2, 0, 350000, 'mfj', 1000, 350000), [4000, 1000, 3000]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 450000, 'mfj', 10000, 30481), [1500, 1500, 0]),
  ('regression joint-threshold 2', (0, 2, 400001, 'mfj', 500, 3000), [950, 500, 0]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0])],
 [('regression joint-threshold 1', (3, 0, 200001, 'mfj', 10000, 24871), [6000, 6000, 0]),
  ('regression joint-threshold 2', (3, 0, 200001, 'mfj', 10000, 30000), [6000, 6000, 0]),
  ('partial repair guard 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('partial repair guard 2', (1, 2, 450000, 'mfj', 0, 10000), [500, 0, 500]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125])],
 [('regression joint-threshold 1', (1, 0, 201000, 'mfj', 0, 2000), [2000, 0, 0]),
  ('regression joint-threshold 2', (2, 1, 275424, 'mfj', 0, 10000), [4500, 0, 1125]),
  ('partial repair guard 1', (3, 2, 450000, 'mfj', 500, 0), [4500, 500, 0]),
  ('partial repair guard 2', (1, 0, 400001, 'mfj', 5000, 42362), [1950, 1950, 0]),
  ('control: earned limit', (1, 0, 30000, 'mfj', 0, 10000), [2000, 0, 1125]),
  ('control: fully phased', (1, 0, 450000, 'mfj', 5000, 450000), [0, 0, 0]),
  ('control: joint partial phase-out', (3, 2, 410500, 'mfj', 1000, 410500), [6450, 1000, 5100]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0])],
 [('regression joint-threshold 1', (2, 0, 405864, 'mfj', 10000, 2000), [3700, 3700, 0]),
  ('regression joint-threshold 2', (1, 0, 201000, 'mfj', 5000, 10000), [2000, 2000, 0]),
  ('partial repair guard 1', (1, 0, 400001, 'mfj', 0, 30000), [1950, 0, 1700]),
  ('partial repair guard 2', (3, 2, 450000, 'mfj', 5000, 30000), [4500, 4500, 0]),
  ('control: other dependents only', (0, 3, 50000, 'single', 0, 50000), [1500, 0, 0]),
  ('control: low earner', (2, 0, 2000, 'single', 0, 2000), [4000, 0, 0]),
  ('control: refund limited by child cap', (2, 0, 150000, 'single', 1000, 30000), [4000, 1000, 3000]),
  ('control: fraction thereof', (2, 1, 201001, 'single', 10000, 200000), [4400, 4400, 0])]]
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 fixtureActualExpectedOutcome
regression joint-threshold 1[6450, 1000, 5100][6450, 1000, 5100]Passed
regression joint-threshold 2[4000, 1000, 3000][4000, 1000, 3000]Passed
control: refund limited by child cap[4000, 1000, 3000][4000, 1000, 3000]Passed
control: fraction thereof[4400, 4400, 0][4400, 4400, 0]Passed
control: earned limit[2000, 0, 1125][2000, 0, 1125]Passed
control: fully phased[0, 0, 0][0, 0, 0]Passed

SHA-256 / 7859ba66f54debb7f1a700e1334d079aa76710b287686e7c84fd8a4a0c26d77a

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 2026-09-29T14:47:08.298157+00:00.

Case digest / 56fafbb7fd9172f8a8411c8f650e2d0e64dcf4879392dbfbb0f7b45728021280