FA-60926 / Bond day-count conventions / Open access

Act/Act ISDA year fraction: days are divided by an average 365.25-day year · case 01

Year fractions are close but not equal to the ISDA value for nearly every span.

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

ROOT CAUSE

The per-year split was replaced with a single division by 365.25.

VERIFIED REPAIR

Split by calendar years and divide each piece by its own year length.

Unsuccessful approach: Dividing by 366 only when a 29 February occurs in the span is a different convention.

Case contract

Inputs start and end [y,m,d]. If end < start return "end before start". Split the interval at each 1 January; each piece contributes its actual days divided by 366 if the piece lies in a Gregorian leap year, else 365. Sum exactly and return the float rounded to 9 decimals.

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
import datetime
from fractions import Fraction
N = 1
observations = []
def solve(a, b):
    A = datetime.date(*a)
    B = datetime.date(*b)
    if B < A:
        return 'end before start'
    def leap(y):
        return (y % 4 == 0 and y % 100 != 0) or y % 400 == 0
    total = Fraction(0)
    cur = A
    total = Fraction((B - A).days * 4, 1461)
    return round(float(total), 9)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression average year basis 1', [[2033, 2, 27], [2036, 11, 26]], 3.745474961], ['regression average year basis 2', [[1897, 9, 30], [1898, 3, 28]], 0.490410959], ['partial repair probe 1', [[2079, 11, 3], [2083, 11, 3]], 4.0], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2059, 8, 30], [2059, 7, 23]], 'end before start'], ['normal control 2', [[2099, 12, 16], [2099, 11, 17]], 'end before start'], ['normal control 3', [[2103, 6, 16], [2103, 5, 8]], 'end before start'], ['normal control 4', [[1990, 7, 22], [1990, 7, 4]], 'end before start']], [['regression average year basis 1', [[2041, 1, 23], [2041, 8, 10]], 0.545205479], ['regression average year basis 2', [[1989, 1, 11], [1992, 10, 16]], 3.762220226], ['partial repair probe 1', [[2086, 2, 28], [2090, 1, 22]], 3.898630137], ['partial repair probe 2', [[2028, 12, 24], [2029, 10, 5]], 0.780762033], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2041, 6, 30], [2041, 5, 29]], 'end before start'], ['normal control 2', [[1944, 6, 15], [1944, 5, 27]], 'end before start'], ['normal control 3', [[2087, 4, 19], [2087, 4, 4]], 'end before start']], [['regression average year basis 1', [[2045, 7, 24], [2046, 1, 10]], 0.465753425], ['regression average year basis 2', [[2104, 1, 17], [2104, 7, 25]], 0.519125683], ['partial repair probe 1', [[2096, 12, 31], [2099, 2, 8]], 2.106841829], ['partial repair probe 2', [[1936, 4, 23], [1937, 4, 22]], 0.99536642], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2039, 3, 17], [2039, 2, 26]], 'end before start'], ['normal control 2', [[2031, 11, 17], [2031, 11, 9]], 'end before start'], ['normal control 3', [[2009, 8, 3], [2009, 6, 30]], 'end before start']], [['regression average year basis 1', [[2018, 9, 1], [2019, 9, 29]], 1.076712329], ['regression average year basis 2', [[2094, 2, 28], [2094, 6, 7]], 0.271232877], ['partial repair probe 1', [[1935, 10, 31], [1936, 4, 13]], 0.451283779], ['partial repair probe 2', [[2083, 5, 15], [2084, 6, 1]], 1.048177259], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1908, 12, 13], [1908, 12, 12]], 'end before start'], ['normal control 2', [[1900, 4, 24], [1900, 4, 13]], 'end before start'], ['normal control 3', [[1994, 7, 29], [1994, 7, 14]], 'end before start']], [['regression average year basis 1', [[2058, 8, 14], [2064, 8, 8]], 5.98465454], ['regression average year basis 2', [[1980, 7, 11], [1983, 5, 22]], 2.861711206], ['partial repair probe 1', [[2088, 5, 30], [2088, 6, 2]], 0.008196721], ['partial repair probe 2', [[2027, 1, 9], [2032, 10, 24]], 5.789557602], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2043, 5, 31], [2043, 4, 25]], 'end before start'], ['normal control 2', [[1960, 8, 1], [1960, 6, 27]], 'end before start'], ['normal control 3', [[2078, 1, 31], [2078, 1, 7]], 'end before start']]]
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 average year basis 1	`3.745379877`	`3.745474961`	Failed
regression average year basis 2	`0.490075291`	`0.490410959`	Failed
partial repair probe 1	`4.0`	`4.0`	Passed
boundary control 1	`0.0`	`0.0`	Passed
normal control 1	`end before start`	`end before start`	Passed
normal control 2	`end before start`	`end before start`	Passed
normal control 3	`end before start`	`end before start`	Passed
normal control 4	`end before start`	`end before start`	Passed

SHA-256 / 0b45a0098e0f6503645534ab7a38d48ca873144c4fe554df758a7579322b4c49

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
from fractions import Fraction
N = 1
observations = []
def solve(a, b):
    A = datetime.date(*a)
    B = datetime.date(*b)
    if B < A:
        return 'end before start'
    def leap(y):
        return (y % 4 == 0 and y % 100 != 0) or y % 400 == 0
    total = Fraction(0)
    cur = A
    has29 = any(leap(y) and A < datetime.date(y, 2, 29) <= B for y in range(A.year, B.year + 1))
    total = Fraction((B - A).days, 366 if has29 else 365)
    return round(float(total), 9)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression average year basis 1', [[2033, 2, 27], [2036, 11, 26]], 3.745474961], ['regression average year basis 2', [[1897, 9, 30], [1898, 3, 28]], 0.490410959], ['partial repair probe 1', [[2079, 11, 3], [2083, 11, 3]], 4.0], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2059, 8, 30], [2059, 7, 23]], 'end before start'], ['normal control 2', [[2099, 12, 16], [2099, 11, 17]], 'end before start'], ['normal control 3', [[2103, 6, 16], [2103, 5, 8]], 'end before start'], ['normal control 4', [[1990, 7, 22], [1990, 7, 4]], 'end before start']], [['regression average year basis 1', [[2041, 1, 23], [2041, 8, 10]], 0.545205479], ['regression average year basis 2', [[1989, 1, 11], [1992, 10, 16]], 3.762220226], ['partial repair probe 1', [[2086, 2, 28], [2090, 1, 22]], 3.898630137], ['partial repair probe 2', [[2028, 12, 24], [2029, 10, 5]], 0.780762033], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2041, 6, 30], [2041, 5, 29]], 'end before start'], ['normal control 2', [[1944, 6, 15], [1944, 5, 27]], 'end before start'], ['normal control 3', [[2087, 4, 19], [2087, 4, 4]], 'end before start']], [['regression average year basis 1', [[2045, 7, 24], [2046, 1, 10]], 0.465753425], ['regression average year basis 2', [[2104, 1, 17], [2104, 7, 25]], 0.519125683], ['partial repair probe 1', [[2096, 12, 31], [2099, 2, 8]], 2.106841829], ['partial repair probe 2', [[1936, 4, 23], [1937, 4, 22]], 0.99536642], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2039, 3, 17], [2039, 2, 26]], 'end before start'], ['normal control 2', [[2031, 11, 17], [2031, 11, 9]], 'end before start'], ['normal control 3', [[2009, 8, 3], [2009, 6, 30]], 'end before start']], [['regression average year basis 1', [[2018, 9, 1], [2019, 9, 29]], 1.076712329], ['regression average year basis 2', [[2094, 2, 28], [2094, 6, 7]], 0.271232877], ['partial repair probe 1', [[1935, 10, 31], [1936, 4, 13]], 0.451283779], ['partial repair probe 2', [[2083, 5, 15], [2084, 6, 1]], 1.048177259], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1908, 12, 13], [1908, 12, 12]], 'end before start'], ['normal control 2', [[1900, 4, 24], [1900, 4, 13]], 'end before start'], ['normal control 3', [[1994, 7, 29], [1994, 7, 14]], 'end before start']], [['regression average year basis 1', [[2058, 8, 14], [2064, 8, 8]], 5.98465454], ['regression average year basis 2', [[1980, 7, 11], [1983, 5, 22]], 2.861711206], ['partial repair probe 1', [[2088, 5, 30], [2088, 6, 2]], 0.008196721], ['partial repair probe 2', [[2027, 1, 9], [2032, 10, 24]], 5.789557602], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2043, 5, 31], [2043, 4, 25]], 'end before start'], ['normal control 2', [[1960, 8, 1], [1960, 6, 27]], 'end before start'], ['normal control 3', [[2078, 1, 31], [2078, 1, 7]], 'end before start']]]
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 average year basis 1	`3.737704918`	`3.745474961`	Failed
regression average year basis 2	`0.490410959`	`0.490410959`	Passed
partial repair probe 1	`3.991803279`	`4.0`	Failed
boundary control 1	`0.0`	`0.0`	Passed
normal control 1	`end before start`	`end before start`	Passed
normal control 2	`end before start`	`end before start`	Passed
normal control 3	`end before start`	`end before start`	Passed
normal control 4	`end before start`	`end before start`	Passed

SHA-256 / eb5d456b920d376fa1ac5c8c73c5b04c602b2caec119b2d94904bb5ed4f40296

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
import datetime
from fractions import Fraction
N = 1
observations = []
def solve(a, b):
    A = datetime.date(*a)
    B = datetime.date(*b)
    if B < A:
        return 'end before start'
    def leap(y):
        return (y % 4 == 0 and y % 100 != 0) or y % 400 == 0
    total = Fraction(0)
    cur = A
    while cur < B:
        nxt = min(B, datetime.date(cur.year + 1, 1, 1))
        total += Fraction((nxt - cur).days, 366 if leap(cur.year) else 365)
        cur = nxt
    return round(float(total), 9)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression average year basis 1', [[2033, 2, 27], [2036, 11, 26]], 3.745474961], ['regression average year basis 2', [[1897, 9, 30], [1898, 3, 28]], 0.490410959], ['partial repair probe 1', [[2079, 11, 3], [2083, 11, 3]], 4.0], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2059, 8, 30], [2059, 7, 23]], 'end before start'], ['normal control 2', [[2099, 12, 16], [2099, 11, 17]], 'end before start'], ['normal control 3', [[2103, 6, 16], [2103, 5, 8]], 'end before start'], ['normal control 4', [[1990, 7, 22], [1990, 7, 4]], 'end before start']], [['regression average year basis 1', [[2041, 1, 23], [2041, 8, 10]], 0.545205479], ['regression average year basis 2', [[1989, 1, 11], [1992, 10, 16]], 3.762220226], ['partial repair probe 1', [[2086, 2, 28], [2090, 1, 22]], 3.898630137], ['partial repair probe 2', [[2028, 12, 24], [2029, 10, 5]], 0.780762033], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2041, 6, 30], [2041, 5, 29]], 'end before start'], ['normal control 2', [[1944, 6, 15], [1944, 5, 27]], 'end before start'], ['normal control 3', [[2087, 4, 19], [2087, 4, 4]], 'end before start']], [['regression average year basis 1', [[2045, 7, 24], [2046, 1, 10]], 0.465753425], ['regression average year basis 2', [[2104, 1, 17], [2104, 7, 25]], 0.519125683], ['partial repair probe 1', [[2096, 12, 31], [2099, 2, 8]], 2.106841829], ['partial repair probe 2', [[1936, 4, 23], [1937, 4, 22]], 0.99536642], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2039, 3, 17], [2039, 2, 26]], 'end before start'], ['normal control 2', [[2031, 11, 17], [2031, 11, 9]], 'end before start'], ['normal control 3', [[2009, 8, 3], [2009, 6, 30]], 'end before start']], [['regression average year basis 1', [[2018, 9, 1], [2019, 9, 29]], 1.076712329], ['regression average year basis 2', [[2094, 2, 28], [2094, 6, 7]], 0.271232877], ['partial repair probe 1', [[1935, 10, 31], [1936, 4, 13]], 0.451283779], ['partial repair probe 2', [[2083, 5, 15], [2084, 6, 1]], 1.048177259], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1908, 12, 13], [1908, 12, 12]], 'end before start'], ['normal control 2', [[1900, 4, 24], [1900, 4, 13]], 'end before start'], ['normal control 3', [[1994, 7, 29], [1994, 7, 14]], 'end before start']], [['regression average year basis 1', [[2058, 8, 14], [2064, 8, 8]], 5.98465454], ['regression average year basis 2', [[1980, 7, 11], [1983, 5, 22]], 2.861711206], ['partial repair probe 1', [[2088, 5, 30], [2088, 6, 2]], 0.008196721], ['partial repair probe 2', [[2027, 1, 9], [2032, 10, 24]], 5.789557602], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2043, 5, 31], [2043, 4, 25]], 'end before start'], ['normal control 2', [[1960, 8, 1], [1960, 6, 27]], 'end before start'], ['normal control 3', [[2078, 1, 31], [2078, 1, 7]], 'end before start']]]
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 average year basis 1	`3.745474961`	`3.745474961`	Passed
regression average year basis 2	`0.490410959`	`0.490410959`	Passed
partial repair probe 1	`4.0`	`4.0`	Passed
boundary control 1	`0.0`	`0.0`	Passed
normal control 1	`end before start`	`end before start`	Passed
normal control 2	`end before start`	`end before start`	Passed
normal control 3	`end before start`	`end before start`	Passed
normal control 4	`end before start`	`end before start`	Passed

SHA-256 / 782187da114c36bf64d2140adcf1cd6a6f6bb9dd856eff91293a9f75f45ba976

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 2026-09-29T14:46:50.250039+00:00.

Case digest / 860770f6cb88f955db6f13f1e04c93012369c446ac4da59eb78bc8edc0d4ed80