FA-60851 / Bond day-count conventions / Open access

30/360 US bond basis: an end date on the last day of February is promoted to 30 on its own · case 01

Periods ending on the last day of February gain days although they started mid-month.

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

ROOT CAUSE

The D2 February rule fires on the end date alone instead of requiring both dates at February end.

THE FAILURE

The D2 February rule fires on the end date alone instead of requiring both dates at February end.

Unsuccessful approach: Additionally requiring the same year blocks the rule for the usual one-year February-to-February span.

Case contract

Inputs are two [year, month, day] dates. Apply, in order: if both dates are the last day of February, D2 becomes 30; if D1 is the last day of February, D1 becomes 30; if D2 is 31 and (adjusted) D1 is 30 or 31, D2 becomes 30; if D1 is 31, D1 becomes 30. Return 360*(Y2-Y1)+30*(M2-M1)+(D2-D1) as an integer day count.

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

N = 1
observations = []
def solve(a, b):
    y1, m1, d1 = a
    y2, m2, d2 = b
    def feb_end(y, m, d):
        leap = (y % 4 == 0 and y % 100 != 0) or y % 400 == 0
        return m == 2 and d == (29 if leap else 28)
    e1 = feb_end(y1, m1, d1)
    e2 = feb_end(y2, m2, d2)
    if e2:
        d2 = 30
    if e1:
        d1 = 30
    if d2 == 31 and d1 >= 30:
        d2 = 30
    if d1 == 31:
        d1 = 30
    return 360 * (y2 - y1) + 30 * (m2 - m1) + (d2 - d1)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression both february ends rule 1', [[2079, 11, 30], [2082, 2, 28]], 808], ['regression both february ends rule 2', [[2004, 2, 28], [2004, 2, 29]], 1], ['partial repair probe 1', [[2096, 2, 29], [2097, 2, 28]], 360], ['partial repair probe 2', [[2004, 2, 29], [2007, 2, 28]], 1080], ['boundary control 1', [[2023, 5, 30], [2023, 7, 31]], 60], ['boundary control 2', [[2024, 1, 1], [2024, 1, 1]], 0], ['normal control 1', [[2029, 12, 31], [2032, 12, 21]], 1071], ['normal control 2', [[2055, 5, 10], [2058, 3, 8]], 1018]], [['regression both february ends rule 1', [[2089, 6, 30], [2091, 2, 28]], 598], ['regression both february ends rule 2', [[2003, 1, 31], [2006, 2, 28]], 1108], ['partial repair probe 1', [[2004, 2, 29], [2006, 2, 28]], 720], ['partial repair probe 2', [[2016, 2, 29], [2017, 2, 28]], 360], ['boundary control 1', [[2023, 2, 28], [2023, 8, 31]], 180], ['boundary control 2', [[2024, 3, 15], [2024, 9, 15]], 180], ['normal control 1', [[2086, 9, 30], [2087, 2, 25]], 145], ['normal control 2', [[2004, 2, 29], [2007, 6, 16]], 1186]], [['regression both february ends rule 1', [[2041, 10, 31], [2042, 2, 28]], 118], ['regression both february ends rule 2', [[2020, 6, 30], [2022, 2, 28]], 598], ['partial repair probe 1', [[2024, 2, 29], [2025, 2, 28]], 360], ['partial repair probe 2', [[2096, 2, 29], [2098, 2, 28]], 720], ['boundary control 1', [[2024, 3, 15], [2024, 9, 15]], 180], ['boundary control 2', [[2024, 1, 1], [2024, 1, 1]], 0], ['normal control 1', [[2041, 2, 28], [2041, 10, 31]], 240], ['normal control 2', [[2032, 9, 8], [2034, 4, 30]], 592]], [['regression both february ends rule 1', [[2049, 10, 31], [2050, 2, 28]], 118], ['regression both february ends rule 2', [[2058, 10, 31], [2059, 2, 28]], 118], ['partial repair probe 1', [[2096, 2, 29], [2099, 2, 28]], 1080], ['partial repair probe 2', [[2000, 2, 29], [2001, 2, 28]], 360], ['boundary control 1', [[2024, 3, 15], [2024, 9, 15]], 180], ['boundary control 2', [[2023, 2, 28], [2023, 8, 31]], 180], ['normal control 1', [[2004, 11, 30], [2004, 11, 30]], 0], ['normal control 2', [[2039, 7, 8], [2042, 10, 31]], 1193]], [['regression both february ends rule 1', [[2014, 6, 30], [2014, 2, 28]], -122], ['regression both february ends rule 2', [[2094, 12, 1], [2096, 2, 29]], 448], ['partial repair probe 1', [[2024, 2, 29], [2026, 2, 28]], 720], ['partial repair probe 2', [[2016, 2, 29], [2018, 2, 28]], 720], ['boundary control 1', [[2023, 5, 30], [2023, 7, 31]], 60], ['boundary control 2', [[2023, 1, 31], [2023, 3, 31]], 60], ['normal control 1', [[2022, 5, 30], [2025, 3, 14]], 1004], ['normal control 2', [[2053, 8, 31], [2054, 3, 18]], 198]]]
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 both february ends rule 1	`810`	`808`	Failed
regression both february ends rule 2	`2`	`1`	Failed
partial repair probe 1	`360`	`360`	Passed
partial repair probe 2	`1080`	`1080`	Passed
boundary control 1	`60`	`60`	Passed
boundary control 2	`0`	`0`	Passed
normal control 1	`1071`	`1071`	Passed
normal control 2	`1018`	`1018`	Passed

SHA-256 / 04bcb52b52a11e4922a3ddca0ff4ed65ea817d9d37e8cd837518be934ea6d29d

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(a, b):
    y1, m1, d1 = a
    y2, m2, d2 = b
    def feb_end(y, m, d):
        leap = (y % 4 == 0 and y % 100 != 0) or y % 400 == 0
        return m == 2 and d == (29 if leap else 28)
    e1 = feb_end(y1, m1, d1)
    e2 = feb_end(y2, m2, d2)
    if e1 and e2 and y1 == y2:
        d2 = 30
    if e1:
        d1 = 30
    if d2 == 31 and d1 >= 30:
        d2 = 30
    if d1 == 31:
        d1 = 30
    return 360 * (y2 - y1) + 30 * (m2 - m1) + (d2 - d1)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression both february ends rule 1', [[2079, 11, 30], [2082, 2, 28]], 808], ['regression both february ends rule 2', [[2004, 2, 28], [2004, 2, 29]], 1], ['partial repair probe 1', [[2096, 2, 29], [2097, 2, 28]], 360], ['partial repair probe 2', [[2004, 2, 29], [2007, 2, 28]], 1080], ['boundary control 1', [[2023, 5, 30], [2023, 7, 31]], 60], ['boundary control 2', [[2024, 1, 1], [2024, 1, 1]], 0], ['normal control 1', [[2029, 12, 31], [2032, 12, 21]], 1071], ['normal control 2', [[2055, 5, 10], [2058, 3, 8]], 1018]], [['regression both february ends rule 1', [[2089, 6, 30], [2091, 2, 28]], 598], ['regression both february ends rule 2', [[2003, 1, 31], [2006, 2, 28]], 1108], ['partial repair probe 1', [[2004, 2, 29], [2006, 2, 28]], 720], ['partial repair probe 2', [[2016, 2, 29], [2017, 2, 28]], 360], ['boundary control 1', [[2023, 2, 28], [2023, 8, 31]], 180], ['boundary control 2', [[2024, 3, 15], [2024, 9, 15]], 180], ['normal control 1', [[2086, 9, 30], [2087, 2, 25]], 145], ['normal control 2', [[2004, 2, 29], [2007, 6, 16]], 1186]], [['regression both february ends rule 1', [[2041, 10, 31], [2042, 2, 28]], 118], ['regression both february ends rule 2', [[2020, 6, 30], [2022, 2, 28]], 598], ['partial repair probe 1', [[2024, 2, 29], [2025, 2, 28]], 360], ['partial repair probe 2', [[2096, 2, 29], [2098, 2, 28]], 720], ['boundary control 1', [[2024, 3, 15], [2024, 9, 15]], 180], ['boundary control 2', [[2024, 1, 1], [2024, 1, 1]], 0], ['normal control 1', [[2041, 2, 28], [2041, 10, 31]], 240], ['normal control 2', [[2032, 9, 8], [2034, 4, 30]], 592]], [['regression both february ends rule 1', [[2049, 10, 31], [2050, 2, 28]], 118], ['regression both february ends rule 2', [[2058, 10, 31], [2059, 2, 28]], 118], ['partial repair probe 1', [[2096, 2, 29], [2099, 2, 28]], 1080], ['partial repair probe 2', [[2000, 2, 29], [2001, 2, 28]], 360], ['boundary control 1', [[2024, 3, 15], [2024, 9, 15]], 180], ['boundary control 2', [[2023, 2, 28], [2023, 8, 31]], 180], ['normal control 1', [[2004, 11, 30], [2004, 11, 30]], 0], ['normal control 2', [[2039, 7, 8], [2042, 10, 31]], 1193]], [['regression both february ends rule 1', [[2014, 6, 30], [2014, 2, 28]], -122], ['regression both february ends rule 2', [[2094, 12, 1], [2096, 2, 29]], 448], ['partial repair probe 1', [[2024, 2, 29], [2026, 2, 28]], 720], ['partial repair probe 2', [[2016, 2, 29], [2018, 2, 28]], 720], ['boundary control 1', [[2023, 5, 30], [2023, 7, 31]], 60], ['boundary control 2', [[2023, 1, 31], [2023, 3, 31]], 60], ['normal control 1', [[2022, 5, 30], [2025, 3, 14]], 1004], ['normal control 2', [[2053, 8, 31], [2054, 3, 18]], 198]]]
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 both february ends rule 1	`808`	`808`	Passed
regression both february ends rule 2	`1`	`1`	Passed
partial repair probe 1	`358`	`360`	Failed
partial repair probe 2	`1078`	`1080`	Failed
boundary control 1	`60`	`60`	Passed
boundary control 2	`0`	`0`	Passed
normal control 1	`1071`	`1071`	Passed
normal control 2	`1018`	`1018`	Passed

SHA-256 / 91cafa47fb64541e7e86279128eda97a22bb2810793796b4a14e14e3ee477c77

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 2026-09-29T14:46:49.464542+00:00.

Case digest / a5335e49428f34b5ba06f03e2255c8187641863653028a0b760b6c5790a15568