FA-61136 / Bond day-count conventions / Open access

Inflation-linked reference index interpolation: the day weight divides by the previous month length · case 01

Interpolation weights are wrong in months whose length differs from the prior month.

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

ROOT CAUSE

The days-in-month divisor is taken from the month before the valuation month.

THE FAILURE

The days-in-month divisor is taken from the month before the valuation month.

Unsuccessful approach: A fixed 30-day divisor is still wrong for 28, 29 and 31 day months.

Case contract

Inputs a date [y,m,d], a map "YYYY-MM" to CPI level and a base index. RefCPI = CPI(m-3) + (d-1)/days_in_month(m) * (CPI(m-2) - CPI(m-3)), computed in Decimal and rounded half-up to 5 decimals; the index ratio is RefCPI/base rounded half-up to 5 decimals. Return both as strings.

Why this case matters

Bond accrual and pricing systems depend on exact day-count arithmetic; a single-day error changes settlement cash.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from decimal import Decimal, ROUND_HALF_UP, ROUND_DOWN
N = 1
observations = []
def solve(date, cpi, base):
    y, m, d = date
    def key(k):
        t = y * 12 + (m - 1) - k
        return '%04d-%02d' % (t // 12, t % 12 + 1)
    def mlen(yy, mm):
        if mm == 2:
            return 29 if (yy % 4 == 0 and yy % 100 != 0) or yy % 400 == 0 else 28
        return 30 if mm in (4, 6, 9, 11) else 31
    c3 = Decimal(str(cpi[key(3)]))
    c2 = Decimal(str(cpi[key(2)]))
    ref = c3 + Decimal(d - 1) / Decimal(mlen(y if m > 1 else y - 1, m - 1 if m > 1 else 12)) * (c2 - c3)
    q = Decimal('0.00001')
    ref = ref.quantize(q, rounding=ROUND_HALF_UP)
    ratio = (ref / Decimal(str(base))).quantize(q, rounding=ROUND_HALF_UP)
    return [str(ref), str(ratio)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression interpolation month length 1', [[2019, 6, 30], {'2019-01': 309.695, '2019-02': 310.077, '2019-03': 309.832, '2019-04': 311.314, '2019-05': 310.87}, 238.98479], ['311.26460', '1.30245']], ['regression interpolation month length 2', [[2023, 12, 15], {'2023-07': 286.241, '2023-08': 285.66, '2023-09': 286.527, '2023-10': 287.196, '2023-11': 286.913}, 284.15717], ['286.82913', '1.00940']], ['partial repair probe 1', [[2023, 8, 31], {'2023-03': 291.685, '2023-04': 293.218, '2023-05': 293.347, '2023-06': 294.41, '2023-07': 295.459}, 285.43104], ['294.37571', '1.03134']], ['partial repair probe 2', [[2029, 8, 15], {'2029-03': 302.449, '2029-04': 303.647, '2029-05': 304.614, '2029-06': 303.989, '2029-07': 304.309}, 212.9858], ['304.33174', '1.42888']], ['normal control 1', [[2026, 2, 1], {'2025-09': 315.84, '2025-10': 315.439, '2025-11': 315.66, '2025-12': 315.118, '2026-01': 315.455}, 203.06179], ['315.66000', '1.55450']], ['normal control 2', [[2031, 9, 1], {'2031-04': 271.482, '2031-05': 270.946, '2031-06': 271.214, '2031-07': 272.455, '2031-08': 274.026}, 283.48158], ['271.21400', '0.95673']], ['normal control 3', [[2030, 3, 1], {'2029-10': 282.052, '2029-11': 282.168, '2029-12': 283.626, '2030-01': 284.046, '2030-02': 285.646}, 232.96031], ['283.62600', '1.21749']], ['normal control 4', [[2013, 4, 1], {'2012-11': 281.431, '2012-12': 281.168, '2013-01': 281.806, '2013-02': 282.137, '2013-03': 282.454}, 183.52015], ['281.80600', '1.53556']]], [['regression interpolation month length 1', [[2014, 10, 31], {'2014-05': 294.459, '2014-06': 294.839, '2014-07': 295.496, '2014-08': 295.793, '2014-09': 296.977}, 251.98063], ['295.78342', '1.17383']], ['regression interpolation month length 2', [[2031, 3, 31], {'2030-10': 226.105, '2030-11': 226.134, '2030-12': 226.176, '2031-01': 226.634, '2031-02': 226.513}, 257.22263], ['226.61923', '0.88102']], ['partial repair probe 1', [[2029, 8, 15], {'2029-03': 268.554, '2029-04': 269.6, '2029-05': 270.75, '2029-06': 271.411, '2029-07': 271.132}, 199.11862], ['271.04852', '1.36124']], ['partial repair probe 2', [[2028, 8, 15], {'2028-03': 266.619, '2028-04': 267.788, '2028-05': 269.082, '2028-06': 268.776, '2028-07': 268.495}, 270.25661], ['268.94381', '0.99514']], ['normal control 1', [[2014, 8, 1], {'2014-03': 298.808, '2014-04': 300.265, '2014-05': 299.956, '2014-06': 299.434, '2014-07': 298.663}, 297.7992], ['299.95600', '1.00724']], ['normal control 2', [[2012, 2, 1], {'2011-09': 225.133, '2011-10': 224.386, '2011-11': 224.672, '2011-12': 224.866, '2012-01': 224.755}, 292.34968], ['224.67200', '0.76850']], ['normal control 3', [[2029, 9, 1], {'2029-04': 231.296, '2029-05': 232.516, '2029-06': 232.524, '2029-07': 233.85, '2029-08': 233.219}, 269.01802], ['232.52400', '0.86434']], ['normal control 4', [[2014, 7, 1], {'2014-02': 253.793, '2014-03': 253.598, '2014-04': 253.178, '2014-05': 252.629, '2014-06': 253.24}, 295.67215], ['253.17800', '0.85628']]], [['regression interpolation month length 1', [[2025, 7, 15], {'2025-02': 267.533, '2025-03': 268.292, '2025-04': 268.191, '2025-05': 267.606, '2025-06': 267.95}, 248.88288], ['267.92681', '1.07652']], ['regression interpolation month length 2', [[2013, 6, 30], {'2013-01': 309.071, '2013-02': 309.841, '2013-03': 311.295, '2013-04': 311.81, '2013-05': 313.187}, 212.24462], ['311.79283', '1.46903']], ['partial repair probe 1', [[2012, 1, 31], {'2011-08': 298.312, '2011-09': 299.217, '2011-10': 299.374, '2011-11': 300.515, '2011-12': 301.795}, 284.3349], ['300.47819', '1.05678']], ['partial repair probe 2', [[2025, 1, 31], {'2024-08': 228.21, '2024-09': 229.721, '2024-10': 230.864, '2024-11': 232.432, '2024-12': 233.938}, 252.86506], ['232.38142', '0.91899']], ['normal control 1', [[2026, 1, 1], {'2025-08': 284.483, '2025-09': 283.821, '2025-10': 284.427, '2025-11': 283.75, '2025-12': 283.435}, 289.74306], ['284.42700', '0.98165']], ['normal control 2', [[2027, 2, 1], {'2026-09': 270.594, '2026-10': 270.395, '2026-11': 269.873, '2026-12': 270.038, '2027-01': 271.273}, 277.8889], ['269.87300', '0.97115']], ['normal control 3', [[2012, 8, 1], {'2012-03': 242.249, '2012-04': 243.495, '2012-05': 244.732, '2012-06': 244.459, '2012-07': 245.657}, 238.26474], ['244.73200', '1.02714']], ['normal control 4', [[2023, 11, 1], {'2023-06': 245.132, '2023-07': 245.968, '2023-08': 245.858, '2023-09': 246.307, '2023-10': 247.011}, 190.51086], ['245.85800', '1.29052']]], [['regression interpolation month length 1', [[2012, 5, 15], {'2011-12': 267.087, '2012-01': 267.9, '2012-02': 267.57, '2012-03': 268.638, '2012-04': 269.447}, 224.03007], ['268.05232', '1.19650']], ['regression interpolation month length 2', [[2030, 12, 9], {'2030-07': 224.829, '2030-08': 225.361, '2030-09': 226.718, '2030-10': 227.831, '2030-11': 229.03}, 228.34967], ['227.00523', '0.99411']], ['partial repair probe 1', [[2013, 1, 15], {'2012-08': 277.0, '2012-09': 278.091, '2012-10': 279.128, '2012-11': 279.833, '2012-12': 279.903}, 274.40946], ['279.44639', '1.01836']], ['partial repair probe 2', [[2030, 8, 29], {'2030-03': 285.257, '2030-04': 286.2, '2030-05': 285.563, '2030-06': 285.885, '2030-07': 285.551}, 199.0528], ['285.85384', '1.43607']], ['normal control 1', [[2015, 6, 1], {'2015-01': 306.248, '2015-02': 305.668, '2015-03': 305.341, '2015-04': 304.599, '2015-05': 305.532}, 218.7922], ['305.34100', '1.39558']], ['normal control 2', [[2023, 4, 1], {'2022-11': 236.726, '2022-12': 237.254, '2023-01': 236.632, '2023-02': 235.847, '2023-03': 235.571}, 189.51387], ['236.63200', '1.24863']], ['normal control 3', [[2015, 11, 1], {'2015-06': 301.807, '2015-07': 301.955, '2015-08': 302.018, '2015-09': 301.819, '2015-10': 301.97}, 210.16228], ['302.01800', '1.43707']], ['normal control 4', [[2012, 12, 1], {'2012-07': 260.444, '2012-08': 260.296, '2012-09': 261.785, '2012-10': 261.123, '2012-11': 261.19}, 236.89836], ['261.78500', '1.10505']]], [['regression interpolation month length 1', [[2016, 10, 15], {'2016-05': 313.26, '2016-06': 314.758, '2016-07': 315.79, '2016-08': 316.11, '2016-09': 316.677}, 209.50603], ['315.93452', '1.50800']], ['regression interpolation month length 2', [[2013, 4, 30], {'2012-11': 278.344, '2012-12': 278.271, '2013-01': 277.492, '2013-02': 278.912, '2013-03': 280.204}, 266.9994], ['278.86467', '1.04444']], ['partial repair probe 1', [[2023, 1, 31], {'2022-08': 276.249, '2022-09': 277.459, '2022-10': 278.602, '2022-11': 279.939, '2022-12': 281.444}, 288.42231], ['279.89587', '0.97044']], ['partial repair probe 2', [[2023, 1, 31], {'2022-08': 259.918, '2022-09': 261.321, '2022-10': 262.916, '2022-11': 263.218, '2022-12': 264.042}, 193.99879], ['263.20826', '1.35675']], ['normal control 1', [[2026, 9, 1], {'2026-04': 250.278, '2026-05': 250.094, '2026-06': 251.494, '2026-07': 252.565, '2026-08': 253.753}, 280.41323], ['251.49400', '0.89687']], ['normal control 2', [[2025, 3, 1], {'2024-10': 276.556, '2024-11': 277.957, '2024-12': 278.642, '2025-01': 280.091, '2025-02': 279.747}, 192.48049], ['278.64200', '1.44764']], ['normal control 3', [[2013, 11, 1], {'2013-06': 288.923, '2013-07': 289.355, '2013-08': 288.597, '2013-09': 288.57, '2013-10': 287.958}, 215.81855], ['288.59700', '1.33722']], ['normal control 4', [[2030, 9, 1], {'2030-04': 271.942, '2030-05': 271.513, '2030-06': 272.396, '2030-07': 273.254, '2030-08': 272.651}, 185.80596], ['272.39600', '1.46602']]]]
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 fixture	Actual	Expected	Outcome
regression interpolation month length 1	`['311.21839', '1.30225']`	`['311.26460', '1.30245']`	Failed
regression interpolation month length 2	`['286.83920', '1.00944']`	`['286.82913', '1.00940']`	Failed
partial repair probe 1	`['294.37571', '1.03134']`	`['294.37571', '1.03134']`	Passed
partial repair probe 2	`['304.33174', '1.42888']`	`['304.33174', '1.42888']`	Passed
normal control 1	`['315.66000', '1.55450']`	`['315.66000', '1.55450']`	Passed
normal control 2	`['271.21400', '0.95673']`	`['271.21400', '0.95673']`	Passed
normal control 3	`['283.62600', '1.21749']`	`['283.62600', '1.21749']`	Passed
normal control 4	`['281.80600', '1.53556']`	`['281.80600', '1.53556']`	Passed

SHA-256 / d54594f1b92209a177018668d2a271dd7caf60cc570a935f0377f408b2160793

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from decimal import Decimal, ROUND_HALF_UP, ROUND_DOWN
N = 1
observations = []
def solve(date, cpi, base):
    y, m, d = date
    def key(k):
        t = y * 12 + (m - 1) - k
        return '%04d-%02d' % (t // 12, t % 12 + 1)
    def mlen(yy, mm):
        if mm == 2:
            return 29 if (yy % 4 == 0 and yy % 100 != 0) or yy % 400 == 0 else 28
        return 30 if mm in (4, 6, 9, 11) else 31
    c3 = Decimal(str(cpi[key(3)]))
    c2 = Decimal(str(cpi[key(2)]))
    ref = c3 + Decimal(d - 1) / Decimal(30) * (c2 - c3)
    q = Decimal('0.00001')
    ref = ref.quantize(q, rounding=ROUND_HALF_UP)
    ratio = (ref / Decimal(str(base))).quantize(q, rounding=ROUND_HALF_UP)
    return [str(ref), str(ratio)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression interpolation month length 1', [[2019, 6, 30], {'2019-01': 309.695, '2019-02': 310.077, '2019-03': 309.832, '2019-04': 311.314, '2019-05': 310.87}, 238.98479], ['311.26460', '1.30245']], ['regression interpolation month length 2', [[2023, 12, 15], {'2023-07': 286.241, '2023-08': 285.66, '2023-09': 286.527, '2023-10': 287.196, '2023-11': 286.913}, 284.15717], ['286.82913', '1.00940']], ['partial repair probe 1', [[2023, 8, 31], {'2023-03': 291.685, '2023-04': 293.218, '2023-05': 293.347, '2023-06': 294.41, '2023-07': 295.459}, 285.43104], ['294.37571', '1.03134']], ['partial repair probe 2', [[2029, 8, 15], {'2029-03': 302.449, '2029-04': 303.647, '2029-05': 304.614, '2029-06': 303.989, '2029-07': 304.309}, 212.9858], ['304.33174', '1.42888']], ['normal control 1', [[2026, 2, 1], {'2025-09': 315.84, '2025-10': 315.439, '2025-11': 315.66, '2025-12': 315.118, '2026-01': 315.455}, 203.06179], ['315.66000', '1.55450']], ['normal control 2', [[2031, 9, 1], {'2031-04': 271.482, '2031-05': 270.946, '2031-06': 271.214, '2031-07': 272.455, '2031-08': 274.026}, 283.48158], ['271.21400', '0.95673']], ['normal control 3', [[2030, 3, 1], {'2029-10': 282.052, '2029-11': 282.168, '2029-12': 283.626, '2030-01': 284.046, '2030-02': 285.646}, 232.96031], ['283.62600', '1.21749']], ['normal control 4', [[2013, 4, 1], {'2012-11': 281.431, '2012-12': 281.168, '2013-01': 281.806, '2013-02': 282.137, '2013-03': 282.454}, 183.52015], ['281.80600', '1.53556']]], [['regression interpolation month length 1', [[2014, 10, 31], {'2014-05': 294.459, '2014-06': 294.839, '2014-07': 295.496, '2014-08': 295.793, '2014-09': 296.977}, 251.98063], ['295.78342', '1.17383']], ['regression interpolation month length 2', [[2031, 3, 31], {'2030-10': 226.105, '2030-11': 226.134, '2030-12': 226.176, '2031-01': 226.634, '2031-02': 226.513}, 257.22263], ['226.61923', '0.88102']], ['partial repair probe 1', [[2029, 8, 15], {'2029-03': 268.554, '2029-04': 269.6, '2029-05': 270.75, '2029-06': 271.411, '2029-07': 271.132}, 199.11862], ['271.04852', '1.36124']], ['partial repair probe 2', [[2028, 8, 15], {'2028-03': 266.619, '2028-04': 267.788, '2028-05': 269.082, '2028-06': 268.776, '2028-07': 268.495}, 270.25661], ['268.94381', '0.99514']], ['normal control 1', [[2014, 8, 1], {'2014-03': 298.808, '2014-04': 300.265, '2014-05': 299.956, '2014-06': 299.434, '2014-07': 298.663}, 297.7992], ['299.95600', '1.00724']], ['normal control 2', [[2012, 2, 1], {'2011-09': 225.133, '2011-10': 224.386, '2011-11': 224.672, '2011-12': 224.866, '2012-01': 224.755}, 292.34968], ['224.67200', '0.76850']], ['normal control 3', [[2029, 9, 1], {'2029-04': 231.296, '2029-05': 232.516, '2029-06': 232.524, '2029-07': 233.85, '2029-08': 233.219}, 269.01802], ['232.52400', '0.86434']], ['normal control 4', [[2014, 7, 1], {'2014-02': 253.793, '2014-03': 253.598, '2014-04': 253.178, '2014-05': 252.629, '2014-06': 253.24}, 295.67215], ['253.17800', '0.85628']]], [['regression interpolation month length 1', [[2025, 7, 15], {'2025-02': 267.533, '2025-03': 268.292, '2025-04': 268.191, '2025-05': 267.606, '2025-06': 267.95}, 248.88288], ['267.92681', '1.07652']], ['regression interpolation month length 2', [[2013, 6, 30], {'2013-01': 309.071, '2013-02': 309.841, '2013-03': 311.295, '2013-04': 311.81, '2013-05': 313.187}, 212.24462], ['311.79283', '1.46903']], ['partial repair probe 1', [[2012, 1, 31], {'2011-08': 298.312, '2011-09': 299.217, '2011-10': 299.374, '2011-11': 300.515, '2011-12': 301.795}, 284.3349], ['300.47819', '1.05678']], ['partial repair probe 2', [[2025, 1, 31], {'2024-08': 228.21, '2024-09': 229.721, '2024-10': 230.864, '2024-11': 232.432, '2024-12': 233.938}, 252.86506], ['232.38142', '0.91899']], ['normal control 1', [[2026, 1, 1], {'2025-08': 284.483, '2025-09': 283.821, '2025-10': 284.427, '2025-11': 283.75, '2025-12': 283.435}, 289.74306], ['284.42700', '0.98165']], ['normal control 2', [[2027, 2, 1], {'2026-09': 270.594, '2026-10': 270.395, '2026-11': 269.873, '2026-12': 270.038, '2027-01': 271.273}, 277.8889], ['269.87300', '0.97115']], ['normal control 3', [[2012, 8, 1], {'2012-03': 242.249, '2012-04': 243.495, '2012-05': 244.732, '2012-06': 244.459, '2012-07': 245.657}, 238.26474], ['244.73200', '1.02714']], ['normal control 4', [[2023, 11, 1], {'2023-06': 245.132, '2023-07': 245.968, '2023-08': 245.858, '2023-09': 246.307, '2023-10': 247.011}, 190.51086], ['245.85800', '1.29052']]], [['regression interpolation month length 1', [[2012, 5, 15], {'2011-12': 267.087, '2012-01': 267.9, '2012-02': 267.57, '2012-03': 268.638, '2012-04': 269.447}, 224.03007], ['268.05232', '1.19650']], ['regression interpolation month length 2', [[2030, 12, 9], {'2030-07': 224.829, '2030-08': 225.361, '2030-09': 226.718, '2030-10': 227.831, '2030-11': 229.03}, 228.34967], ['227.00523', '0.99411']], ['partial repair probe 1', [[2013, 1, 15], {'2012-08': 277.0, '2012-09': 278.091, '2012-10': 279.128, '2012-11': 279.833, '2012-12': 279.903}, 274.40946], ['279.44639', '1.01836']], ['partial repair probe 2', [[2030, 8, 29], {'2030-03': 285.257, '2030-04': 286.2, '2030-05': 285.563, '2030-06': 285.885, '2030-07': 285.551}, 199.0528], ['285.85384', '1.43607']], ['normal control 1', [[2015, 6, 1], {'2015-01': 306.248, '2015-02': 305.668, '2015-03': 305.341, '2015-04': 304.599, '2015-05': 305.532}, 218.7922], ['305.34100', '1.39558']], ['normal control 2', [[2023, 4, 1], {'2022-11': 236.726, '2022-12': 237.254, '2023-01': 236.632, '2023-02': 235.847, '2023-03': 235.571}, 189.51387], ['236.63200', '1.24863']], ['normal control 3', [[2015, 11, 1], {'2015-06': 301.807, '2015-07': 301.955, '2015-08': 302.018, '2015-09': 301.819, '2015-10': 301.97}, 210.16228], ['302.01800', '1.43707']], ['normal control 4', [[2012, 12, 1], {'2012-07': 260.444, '2012-08': 260.296, '2012-09': 261.785, '2012-10': 261.123, '2012-11': 261.19}, 236.89836], ['261.78500', '1.10505']]], [['regression interpolation month length 1', [[2016, 10, 15], {'2016-05': 313.26, '2016-06': 314.758, '2016-07': 315.79, '2016-08': 316.11, '2016-09': 316.677}, 209.50603], ['315.93452', '1.50800']], ['regression interpolation month length 2', [[2013, 4, 30], {'2012-11': 278.344, '2012-12': 278.271, '2013-01': 277.492, '2013-02': 278.912, '2013-03': 280.204}, 266.9994], ['278.86467', '1.04444']], ['partial repair probe 1', [[2023, 1, 31], {'2022-08': 276.249, '2022-09': 277.459, '2022-10': 278.602, '2022-11': 279.939, '2022-12': 281.444}, 288.42231], ['279.89587', '0.97044']], ['partial repair probe 2', [[2023, 1, 31], {'2022-08': 259.918, '2022-09': 261.321, '2022-10': 262.916, '2022-11': 263.218, '2022-12': 264.042}, 193.99879], ['263.20826', '1.35675']], ['normal control 1', [[2026, 9, 1], {'2026-04': 250.278, '2026-05': 250.094, '2026-06': 251.494, '2026-07': 252.565, '2026-08': 253.753}, 280.41323], ['251.49400', '0.89687']], ['normal control 2', [[2025, 3, 1], {'2024-10': 276.556, '2024-11': 277.957, '2024-12': 278.642, '2025-01': 280.091, '2025-02': 279.747}, 192.48049], ['278.64200', '1.44764']], ['normal control 3', [[2013, 11, 1], {'2013-06': 288.923, '2013-07': 289.355, '2013-08': 288.597, '2013-09': 288.57, '2013-10': 287.958}, 215.81855], ['288.59700', '1.33722']], ['normal control 4', [[2030, 9, 1], {'2030-04': 271.942, '2030-05': 271.513, '2030-06': 272.396, '2030-07': 273.254, '2030-08': 272.651}, 185.80596], ['272.39600', '1.46602']]]]
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 fixture	Actual	Expected	Outcome
regression interpolation month length 1	`['311.26460', '1.30245']`	`['311.26460', '1.30245']`	Passed
regression interpolation month length 2	`['286.83920', '1.00944']`	`['286.82913', '1.00940']`	Failed
partial repair probe 1	`['294.41000', '1.03146']`	`['294.37571', '1.03134']`	Failed
partial repair probe 2	`['304.32233', '1.42884']`	`['304.33174', '1.42888']`	Failed
normal control 1	`['315.66000', '1.55450']`	`['315.66000', '1.55450']`	Passed
normal control 2	`['271.21400', '0.95673']`	`['271.21400', '0.95673']`	Passed
normal control 3	`['283.62600', '1.21749']`	`['283.62600', '1.21749']`	Passed
normal control 4	`['281.80600', '1.53556']`	`['281.80600', '1.53556']`	Passed

SHA-256 / 8448b5f7d79c57805bcc94a4a9699083ff95f564d3f8e2b9117c294a57eaadc6

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.

Member access is invitation-based. Sign in with your invited account to inspect the repair.

Verification & scope

A deterministic toy contract stated explicitly in the contract field; no claim of conformance to any published convention text. 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 2026-09-29T14:46:52.402012+00:00.

Case digest / ea4f1f8f07691c8d1a2fbe046caa367e9ec20a915bd2db72aac73dd5b2018c71