FA-60911 / Bond day-count conventions / Open access

Act/Act ISDA year fraction: every calendar piece uses the start year basis · case 01

Spans crossing from a non-leap year into a leap year divide leap-year days by 365.

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

ROOT CAUSE

The denominator is chosen from the start year instead of the year of each piece.

VERIFIED REPAIR

Choose 366 or 365 separately for each calendar-year piece.

Unsuccessful approach: Using the end year basis for all pieces moves the error to the first piece.

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
    while cur < B:
        nxt = min(B, datetime.date(cur.year + 1, 1, 1))
        total += Fraction((nxt - cur).days, 366 if leap(A.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 segment denominator year 1', [[1920, 8, 29], [1921, 12, 9]], 1.278516356], ['regression segment denominator year 2', [[2088, 10, 21], [2093, 8, 9]], 4.799461038], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[2098, 9, 14], [2099, 8, 15]], 0.917808219], ['normal control 2', [[2096, 2, 29], [2096, 6, 22]], 0.31147541]], [['regression segment denominator year 1', [[2049, 10, 8], [2054, 9, 16]], 4.939726027], ['regression segment denominator year 2', [[2091, 8, 29], [2093, 12, 24]], 2.320547945], ['partial repair probe 1', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1898, 2, 10], [1899, 1, 16]], 0.931506849], ['normal control 2', [[1983, 9, 20], [1983, 10, 2]], 0.032876712]], [['regression segment denominator year 1', [[2104, 1, 11], [2109, 3, 18]], 5.180896774], ['regression segment denominator year 2', [[2023, 11, 30], [2026, 10, 31]], 2.917808219], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[1909, 5, 31], [1910, 7, 3]], 1.090410959], ['normal control 2', [[2054, 6, 11], [2054, 5, 11]], 'end before start']], [['regression segment denominator year 1', [[1913, 2, 14], [1916, 9, 4]], 3.554315443], ['regression segment denominator year 2', [[1911, 1, 28], [1916, 3, 20]], 5.141874392], ['partial repair probe 1', [[2023, 12, 30], [2024, 1, 1]], 0.005479452], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2078, 8, 31], [2078, 7, 25]], 'end before start'], ['normal control 2', [[1941, 8, 21], [1942, 1, 26]], 0.432876712]], [['regression segment denominator year 1', [[2056, 7, 19], [2057, 5, 22]], 0.839853282], ['regression segment denominator year 2', [[1938, 2, 28], [1943, 7, 22]], 5.394520548], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2056, 2, 10], [2057, 1, 1]], 0.890710383], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2090, 12, 9], [2091, 10, 25]], 0.876712329], ['normal control 2', [[2031, 7, 31], [2031, 10, 31]], 0.252054795]]]
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 segment denominator year 1	`1.275956284`	`1.278516356`	Failed
regression segment denominator year 2	`4.789617486`	`4.799461038`	Failed
partial repair probe 1	`1.0`	`1.0`	Passed
partial repair probe 2	`0.002739726`	`0.002739726`	Passed
boundary control 1	`0.0`	`0.0`	Passed
boundary control 2	`0.246575342`	`0.246575342`	Passed
normal control 1	`0.917808219`	`0.917808219`	Passed
normal control 2	`0.31147541`	`0.31147541`	Passed

SHA-256 / ca666869288183eda84c957f24ef661ea674f936f74624b135113f1de93ef851

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
    while cur < B:
        nxt = min(B, datetime.date(cur.year + 1, 1, 1))
        total += Fraction((nxt - cur).days, 366 if leap(B.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 segment denominator year 1', [[1920, 8, 29], [1921, 12, 9]], 1.278516356], ['regression segment denominator year 2', [[2088, 10, 21], [2093, 8, 9]], 4.799461038], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[2098, 9, 14], [2099, 8, 15]], 0.917808219], ['normal control 2', [[2096, 2, 29], [2096, 6, 22]], 0.31147541]], [['regression segment denominator year 1', [[2049, 10, 8], [2054, 9, 16]], 4.939726027], ['regression segment denominator year 2', [[2091, 8, 29], [2093, 12, 24]], 2.320547945], ['partial repair probe 1', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1898, 2, 10], [1899, 1, 16]], 0.931506849], ['normal control 2', [[1983, 9, 20], [1983, 10, 2]], 0.032876712]], [['regression segment denominator year 1', [[2104, 1, 11], [2109, 3, 18]], 5.180896774], ['regression segment denominator year 2', [[2023, 11, 30], [2026, 10, 31]], 2.917808219], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[1909, 5, 31], [1910, 7, 3]], 1.090410959], ['normal control 2', [[2054, 6, 11], [2054, 5, 11]], 'end before start']], [['regression segment denominator year 1', [[1913, 2, 14], [1916, 9, 4]], 3.554315443], ['regression segment denominator year 2', [[1911, 1, 28], [1916, 3, 20]], 5.141874392], ['partial repair probe 1', [[2023, 12, 30], [2024, 1, 1]], 0.005479452], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2078, 8, 31], [2078, 7, 25]], 'end before start'], ['normal control 2', [[1941, 8, 21], [1942, 1, 26]], 0.432876712]], [['regression segment denominator year 1', [[2056, 7, 19], [2057, 5, 22]], 0.839853282], ['regression segment denominator year 2', [[1938, 2, 28], [1943, 7, 22]], 5.394520548], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2056, 2, 10], [2057, 1, 1]], 0.890710383], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2090, 12, 9], [2091, 10, 25]], 0.876712329], ['normal control 2', [[2031, 7, 31], [2031, 10, 31]], 0.252054795]]]
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 segment denominator year 1	`1.279452055`	`1.278516356`	Failed
regression segment denominator year 2	`4.802739726`	`4.799461038`	Failed
partial repair probe 1	`1.002739726`	`1.0`	Failed
partial repair probe 2	`0.00273224`	`0.002739726`	Failed
boundary control 1	`0.0`	`0.0`	Passed
boundary control 2	`0.246575342`	`0.246575342`	Passed
normal control 1	`0.917808219`	`0.917808219`	Passed
normal control 2	`0.31147541`	`0.31147541`	Passed

SHA-256 / b27f0915d9598f0c9b61f4bdc8f6fb4c2b4473ce25c532921679809612ab4249

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 segment denominator year 1', [[1920, 8, 29], [1921, 12, 9]], 1.278516356], ['regression segment denominator year 2', [[2088, 10, 21], [2093, 8, 9]], 4.799461038], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[2098, 9, 14], [2099, 8, 15]], 0.917808219], ['normal control 2', [[2096, 2, 29], [2096, 6, 22]], 0.31147541]], [['regression segment denominator year 1', [[2049, 10, 8], [2054, 9, 16]], 4.939726027], ['regression segment denominator year 2', [[2091, 8, 29], [2093, 12, 24]], 2.320547945], ['partial repair probe 1', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[1898, 2, 10], [1899, 1, 16]], 0.931506849], ['normal control 2', [[1983, 9, 20], [1983, 10, 2]], 0.032876712]], [['regression segment denominator year 1', [[2104, 1, 11], [2109, 3, 18]], 5.180896774], ['regression segment denominator year 2', [[2023, 11, 30], [2026, 10, 31]], 2.917808219], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2023, 12, 31], [2024, 1, 1]], 0.002739726], ['boundary control 1', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['boundary control 2', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['normal control 1', [[1909, 5, 31], [1910, 7, 3]], 1.090410959], ['normal control 2', [[2054, 6, 11], [2054, 5, 11]], 'end before start']], [['regression segment denominator year 1', [[1913, 2, 14], [1916, 9, 4]], 3.554315443], ['regression segment denominator year 2', [[1911, 1, 28], [1916, 3, 20]], 5.141874392], ['partial repair probe 1', [[2023, 12, 30], [2024, 1, 1]], 0.005479452], ['partial repair probe 2', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2078, 8, 31], [2078, 7, 25]], 'end before start'], ['normal control 2', [[1941, 8, 21], [1942, 1, 26]], 0.432876712]], [['regression segment denominator year 1', [[2056, 7, 19], [2057, 5, 22]], 0.839853282], ['regression segment denominator year 2', [[1938, 2, 28], [1943, 7, 22]], 5.394520548], ['partial repair probe 1', [[2024, 1, 1], [2025, 1, 1]], 1.0], ['partial repair probe 2', [[2056, 2, 10], [2057, 1, 1]], 0.890710383], ['boundary control 1', [[2099, 12, 1], [2100, 3, 1]], 0.246575342], ['boundary control 2', [[2024, 3, 1], [2024, 3, 1]], 0.0], ['normal control 1', [[2090, 12, 9], [2091, 10, 25]], 0.876712329], ['normal control 2', [[2031, 7, 31], [2031, 10, 31]], 0.252054795]]]
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 segment denominator year 1	`1.278516356`	`1.278516356`	Passed
regression segment denominator year 2	`4.799461038`	`4.799461038`	Passed
partial repair probe 1	`1.0`	`1.0`	Passed
partial repair probe 2	`0.002739726`	`0.002739726`	Passed
boundary control 1	`0.0`	`0.0`	Passed
boundary control 2	`0.246575342`	`0.246575342`	Passed
normal control 1	`0.917808219`	`0.917808219`	Passed
normal control 2	`0.31147541`	`0.31147541`	Passed

SHA-256 / 21bfed50aa3c60f14596cfbe34cc6b57be3519c985582b5004f318ed705875eb

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 2026-09-29T14:46:49.990421+00:00.

Case digest / 9978245080d81978b5b844f66b97bf1fb92633f877e335b509daf99b2fbe3740