FAILURE MAP
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FA-93891 / Shift rostering labor rules / Open access

Gross pay truncates half cents instead of rounding half up · case 01

Pay lines ending in exactly half a cent (or more) lose a cent.

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

ROOT CAUSE

The exact half-cent total is floor-divided.

THE FAILURE

The exact half-cent total is floor-divided.

Unsuccessful approach: Python round() uses banker's rounding, so even-cent halves still round down.

Case contract

Seven daily worked minutes (Mon..Sun) and an hourly rate in cents. Daily: first 480 minutes regular, next 240 at 1.5x, beyond 720 at 2x. If all seven days are worked, day 7 pays its first 480 minutes at 1.5x and the rest at 2x. Regular minutes above 2400 in the week move to 1.5x (daily overtime minutes never count toward the weekly threshold). Pay is computed exactly and rounded half up to a cent once. Return [regular, ot15, ot2, pay_cents].

Why this case matters

Overtime classification mistakes are a classic payroll-roster defect: pyramiding, seventh-day rules and rounding stage all change what workers are paid.

1 / The failure

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

N = 1
observations = []
def solve(days, rate):
    reg = ot15 = ot2 = 0
    seventh = all(m > 0 for m in days)
    for d, m in enumerate(days):
        if d == 6 and seventh:
            ot15 += min(m, 480)
            ot2 += max(m - 480, 0)
            continue
        reg += min(m, 480)
        ot15 += min(max(m - 480, 0), 240)
        ot2 += max(m - 720, 0)
    excess = max(reg - 2400, 0)
    reg -= excess
    ot15 += excess
    units = reg * rate * 2 + ot15 * rate * 3 + ot2 * rate * 4
    pay = units // 120
    return [reg, ot15, ot2, pay]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: pay rounding mode 1', [[9, 0, 0, 0, 0, 0, 0], 30], [9, 0, 0, 5]),
  ('regression variant: pay rounding mode 2', [[480, 300, 600, 300, 510, 600, 480], 90],
   [2400, 870, 0, 5558]),
  ('partial repair guard 3', [[900, 0, 480, 600, 165, 0, 540], 2250], [2085, 420, 180, 115313]),
  ('boundary control 4', [[480, 480, 480, 480, 480, 480, 0], 2000], [2400, 480, 0, 104000]),
  ('normal control 5', [[0, 600, 480, 480, 900, 600, 780], 30], [2400, 1200, 240, 2340]),
  ('normal control 6', [[480, 481, 721, 600, 540, 546, 900], 2250], [2400, 1447, 421, 202969]),
  ('normal control 7', [[300, 480, 480, 300, 510, 300, 480], 90], [2340, 510, 0, 4658]),
  ('normal control 8', [[510, 510, 600, 480, 300, 600, 480], 1725], [2400, 1080, 0, 115575])],
 [('regression: pay rounding mode 1', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('regression variant: pay rounding mode 2', [[721, 450, 477, 0, 0, 900, 480], 90], [2367, 480, 181, 5174]),
  ('partial repair guard 3', [[240, 600, 0, 780, 450, 900, 900], 90], [2400, 1050, 420, 7223]),
  ('boundary control 4', [[0, 480, 480, 480, 480, 480, 480], 1500], [2400, 480, 0, 78000]),
  ('boundary control 5', [[480, 480, 480, 480, 480, 480, 0], 2000], [2400, 480, 0, 104000]),
  ('normal control 6', [[0, 780, 600, 480, 480, 240, 721], 2250], [2400, 840, 61, 141825]),
  ('normal control 7', [[480, 600, 510, 480, 600, 510, 510], 30], [2400, 1260, 30, 2175]),
  ('normal control 8', [[721, 540, 0, 600, 480, 540, 0], 2250], [2400, 480, 1, 117075])],
 [('regression: pay rounding mode 1', [[300, 600, 300, 600, 510, 600, 480], 90], [2400, 990, 0, 5828]),
  ('regression variant: pay rounding mode 2', [[300, 600, 480, 300, 600, 600, 300], 1725],
   [2400, 780, 0, 102638]),
  ('partial repair guard 3', [[510, 300, 300, 600, 600, 300, 510], 30], [2340, 750, 30, 1763]),
  ('boundary control 4', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('boundary control 5', [[0, 480, 480, 480, 480, 480, 480], 1500], [2400, 480, 0, 78000]),
  ('normal control 6', [[0, 0, 481, 780, 874, 721, 92], 30], [2012, 721, 215, 1762]),
  ('normal control 7', [[481, 0, 900, 240, 540, 900, 480], 2250], [2400, 781, 360, 160931]),
  ('normal control 8', [[0, 450, 480, 600, 240, 540, 720], 1500], [2400, 630, 0, 83625])],
 [('regression: pay rounding mode 1', [[300, 600, 480, 600, 480, 510, 510], 90], [2400, 1050, 30, 6053]),
  ('regression variant: pay rounding mode 2', [[900, 720, 0, 480, 450, 240, 600], 2250],
   [2400, 810, 180, 149063]),
  ('partial repair guard 3', [[510, 510, 510, 510, 480, 510, 300], 2250], [2400, 930, 0, 142313]),
  ('boundary control 4', [[600, 600, 600, 600, 600, 0, 0], 1500], [2400, 600, 0, 82500]),
  ('boundary control 5', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('normal control 6', [[300, 480, 300, 300, 480, 600, 600], 2250], [2340, 600, 120, 130500]),
  ('normal control 7', [[720, 780, 720, 540, 450, 900, 721], 1500], [2400, 1950, 481, 157175]),
  ('normal control 8', [[300, 300, 480, 510, 510, 600, 600], 1500], [2400, 780, 120, 95250])],
 [('regression: pay rounding mode 1', [[481, 119, 900, 256, 240, 20, 480], 2000], [1595, 721, 180, 101217]),
  ('regression variant: pay rounding mode 2', [[780, 450, 900, 900, 780, 900, 780], 1810],
   [2400, 2130, 960, 226703]),
  ('partial repair guard 3', [[240, 600, 240, 13, 780, 0, 540], 90], [1933, 420, 60, 4025]),
  ('boundary control 4', [[540, 540, 540, 540, 540, 540, 60], 2000], [2400, 900, 0, 125000]),
  ('boundary control 5', [[600, 600, 600, 600, 600, 0, 0], 1500], [2400, 600, 0, 82500]),
  ('normal control 6', [[0, 240, 721, 751, 481, 900, 0], 1810], [2160, 721, 212, 110576]),
  ('normal control 7', [[600, 600, 600, 480, 600, 600, 600], 1810], [2400, 1560, 120, 150230]),
  ('normal control 8', [[481, 900, 720, 481, 540, 540, 0], 1725], [2400, 1082, 180, 126011])]]
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: pay rounding mode 1[9, 0, 0, 4][9, 0, 0, 5]Failed
regression variant: pay rounding mode 2[2400, 870, 0, 5557][2400, 870, 0, 5558]Failed
partial repair guard 3[2085, 420, 180, 115312][2085, 420, 180, 115313]Failed
boundary control 4[2400, 480, 0, 104000][2400, 480, 0, 104000]Passed
normal control 5[2400, 1200, 240, 2340][2400, 1200, 240, 2340]Passed
normal control 6[2400, 1447, 421, 202968][2400, 1447, 421, 202969]Failed
normal control 7[2340, 510, 0, 4657][2340, 510, 0, 4658]Failed
normal control 8[2400, 1080, 0, 115575][2400, 1080, 0, 115575]Passed

SHA-256 / 8883c232bc98449674096942fe7e5089698ef5a2659b97a43c7dbbbf97b6663c

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(days, rate):
    reg = ot15 = ot2 = 0
    seventh = all(m > 0 for m in days)
    for d, m in enumerate(days):
        if d == 6 and seventh:
            ot15 += min(m, 480)
            ot2 += max(m - 480, 0)
            continue
        reg += min(m, 480)
        ot15 += min(max(m - 480, 0), 240)
        ot2 += max(m - 720, 0)
    excess = max(reg - 2400, 0)
    reg -= excess
    ot15 += excess
    units = reg * rate * 2 + ot15 * rate * 3 + ot2 * rate * 4
    pay = round(units / 120)
    return [reg, ot15, ot2, pay]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: pay rounding mode 1', [[9, 0, 0, 0, 0, 0, 0], 30], [9, 0, 0, 5]),
  ('regression variant: pay rounding mode 2', [[480, 300, 600, 300, 510, 600, 480], 90],
   [2400, 870, 0, 5558]),
  ('partial repair guard 3', [[900, 0, 480, 600, 165, 0, 540], 2250], [2085, 420, 180, 115313]),
  ('boundary control 4', [[480, 480, 480, 480, 480, 480, 0], 2000], [2400, 480, 0, 104000]),
  ('normal control 5', [[0, 600, 480, 480, 900, 600, 780], 30], [2400, 1200, 240, 2340]),
  ('normal control 6', [[480, 481, 721, 600, 540, 546, 900], 2250], [2400, 1447, 421, 202969]),
  ('normal control 7', [[300, 480, 480, 300, 510, 300, 480], 90], [2340, 510, 0, 4658]),
  ('normal control 8', [[510, 510, 600, 480, 300, 600, 480], 1725], [2400, 1080, 0, 115575])],
 [('regression: pay rounding mode 1', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('regression variant: pay rounding mode 2', [[721, 450, 477, 0, 0, 900, 480], 90], [2367, 480, 181, 5174]),
  ('partial repair guard 3', [[240, 600, 0, 780, 450, 900, 900], 90], [2400, 1050, 420, 7223]),
  ('boundary control 4', [[0, 480, 480, 480, 480, 480, 480], 1500], [2400, 480, 0, 78000]),
  ('boundary control 5', [[480, 480, 480, 480, 480, 480, 0], 2000], [2400, 480, 0, 104000]),
  ('normal control 6', [[0, 780, 600, 480, 480, 240, 721], 2250], [2400, 840, 61, 141825]),
  ('normal control 7', [[480, 600, 510, 480, 600, 510, 510], 30], [2400, 1260, 30, 2175]),
  ('normal control 8', [[721, 540, 0, 600, 480, 540, 0], 2250], [2400, 480, 1, 117075])],
 [('regression: pay rounding mode 1', [[300, 600, 300, 600, 510, 600, 480], 90], [2400, 990, 0, 5828]),
  ('regression variant: pay rounding mode 2', [[300, 600, 480, 300, 600, 600, 300], 1725],
   [2400, 780, 0, 102638]),
  ('partial repair guard 3', [[510, 300, 300, 600, 600, 300, 510], 30], [2340, 750, 30, 1763]),
  ('boundary control 4', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('boundary control 5', [[0, 480, 480, 480, 480, 480, 480], 1500], [2400, 480, 0, 78000]),
  ('normal control 6', [[0, 0, 481, 780, 874, 721, 92], 30], [2012, 721, 215, 1762]),
  ('normal control 7', [[481, 0, 900, 240, 540, 900, 480], 2250], [2400, 781, 360, 160931]),
  ('normal control 8', [[0, 450, 480, 600, 240, 540, 720], 1500], [2400, 630, 0, 83625])],
 [('regression: pay rounding mode 1', [[300, 600, 480, 600, 480, 510, 510], 90], [2400, 1050, 30, 6053]),
  ('regression variant: pay rounding mode 2', [[900, 720, 0, 480, 450, 240, 600], 2250],
   [2400, 810, 180, 149063]),
  ('partial repair guard 3', [[510, 510, 510, 510, 480, 510, 300], 2250], [2400, 930, 0, 142313]),
  ('boundary control 4', [[600, 600, 600, 600, 600, 0, 0], 1500], [2400, 600, 0, 82500]),
  ('boundary control 5', [[27, 0, 0, 0, 0, 0, 0], 30], [27, 0, 0, 14]),
  ('normal control 6', [[300, 480, 300, 300, 480, 600, 600], 2250], [2340, 600, 120, 130500]),
  ('normal control 7', [[720, 780, 720, 540, 450, 900, 721], 1500], [2400, 1950, 481, 157175]),
  ('normal control 8', [[300, 300, 480, 510, 510, 600, 600], 1500], [2400, 780, 120, 95250])],
 [('regression: pay rounding mode 1', [[481, 119, 900, 256, 240, 20, 480], 2000], [1595, 721, 180, 101217]),
  ('regression variant: pay rounding mode 2', [[780, 450, 900, 900, 780, 900, 780], 1810],
   [2400, 2130, 960, 226703]),
  ('partial repair guard 3', [[240, 600, 240, 13, 780, 0, 540], 90], [1933, 420, 60, 4025]),
  ('boundary control 4', [[540, 540, 540, 540, 540, 540, 60], 2000], [2400, 900, 0, 125000]),
  ('boundary control 5', [[600, 600, 600, 600, 600, 0, 0], 1500], [2400, 600, 0, 82500]),
  ('normal control 6', [[0, 240, 721, 751, 481, 900, 0], 1810], [2160, 721, 212, 110576]),
  ('normal control 7', [[600, 600, 600, 480, 600, 600, 600], 1810], [2400, 1560, 120, 150230]),
  ('normal control 8', [[481, 900, 720, 481, 540, 540, 0], 1725], [2400, 1082, 180, 126011])]]
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: pay rounding mode 1[9, 0, 0, 4][9, 0, 0, 5]Failed
regression variant: pay rounding mode 2[2400, 870, 0, 5558][2400, 870, 0, 5558]Passed
partial repair guard 3[2085, 420, 180, 115312][2085, 420, 180, 115313]Failed
boundary control 4[2400, 480, 0, 104000][2400, 480, 0, 104000]Passed
normal control 5[2400, 1200, 240, 2340][2400, 1200, 240, 2340]Passed
normal control 6[2400, 1447, 421, 202969][2400, 1447, 421, 202969]Passed
normal control 7[2340, 510, 0, 4658][2340, 510, 0, 4658]Passed
normal control 8[2400, 1080, 0, 115575][2400, 1080, 0, 115575]Passed

SHA-256 / 0465fc0f7bb65b4221bcb66731938e163b8ce9b5a79cf04a85ff407579ea30f2

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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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 2026-09-29T14:51:59.344909+00:00.

Case digest / a9af15265b722905bcde0fe98ab41743f7ded3325489c5f0eb86936afed4498f