FAILURE MAP
← Case archive

FA-58566 / Loan amortization schedules / Open access

Adjustable rate reset with caps: cap reference rate · case 01

Later resets jump by more than the periodic cap from the prior note rate.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Caps are measured from the previous fully indexed rate instead of the previous note rate.

THE FAILURE

Caps are measured from the previous fully indexed rate instead of the previous note rate.

Unsuccessful approach: Measuring from the initial rate caps every reset relative to the start rate.

Case contract

x = {'initial_bp', 'index_path': index at each reset, 'margin_bp', 'round_to', 'initial_cap_bp', 'periodic_cap_bp', 'lifetime_cap_bp' (above initial), 'floor_bp'}. At each reset the fully indexed rate index + margin is rounded half-up to a multiple of round_to, limited to within the cap of the previous note rate (initial cap at the first reset, periodic afterwards, both directions), then limited to [floor_bp, initial + lifetime cap]. Return the list of note rates.

Why this case matters

Amortization engines drive borrower statements, payoff quotes and investor remittances; a misplaced rounding step, boundary or ordering rule compounds across hundreds of periods.

1 / The failure

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

N = 1
observations = []
def solve(x):
    rate = x['initial_bp']
    out = []
    life_max = x['initial_bp'] + x['lifetime_cap_bp']
    for i, idx in enumerate(x['index_path']):
        fi = idx + x['margin_bp']
        q, r = divmod(fi, x['round_to'])
        fi = (q + (1 if 2 * r >= x['round_to'] else 0)) * x['round_to']
        cap = x['initial_cap_bp'] if i == 0 else x['periodic_cap_bp']
        new = max(rate - cap, min(fi, rate + cap))
        new = max(x['floor_bp'], min(new, life_max))
        out.append(new)
        rate = fi
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: cap reference rate', {'initial_bp': 500, 'index_path': [212, 100, 50, 250, 700], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 400, 400, 500, 600]], ['regression: cap reference rate, partial-repair probe', {'initial_bp': 450, 'index_path': [250, 650, 100, 650, 650], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [475, 575, 475, 575, 675]], ['control 1', {'initial_bp': 500, 'index_path': [650], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [875]], ['control 2', {'initial_bp': 300, 'index_path': [212, 212], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [475, 475]], ['control 3', {'initial_bp': 300, 'index_path': [100, 50, 250], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [400, 350, 550]], ['control 4', {'initial_bp': 450, 'index_path': [50, 100], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [300, 325]], ['control 5', {'initial_bp': 500, 'index_path': [700], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [700]]], [['regression: cap reference rate', {'initial_bp': 450, 'index_path': [650, 50, 212], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [650, 550, 500]], ['control 1', {'initial_bp': 500, 'index_path': [537, 650, 250, 400, 537], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [700, 875, 675, 625, 750]], ['control 2', {'initial_bp': 450, 'index_path': [250, 100, 700], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [475, 325, 525]], ['control 3', {'initial_bp': 450, 'index_path': [400, 700], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [625, 825]], ['control 4', {'initial_bp': 500, 'index_path': [212], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [375]], ['control 5', {'initial_bp': 300, 'index_path': [250], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [525]], ['control 6', {'initial_bp': 450, 'index_path': [50], 'margin_bp': 250, 'round_to': 50, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [400]]], [['regression: cap reference rate', {'initial_bp': 450, 'index_path': [212, 650, 50, 650], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [500, 700, 500, 700]], ['control 1', {'initial_bp': 450, 'index_path': [250, 250, 212], 'margin_bp': 225, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [500, 500, 450]], ['control 2', {'initial_bp': 450, 'index_path': [100], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [400]], ['control 3', {'initial_bp': 500, 'index_path': [700, 250], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [1000, 900]], ['control 4', {'initial_bp': 500, 'index_path': [212, 537], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 700]], ['control 5', {'initial_bp': 450, 'index_path': [400, 50], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [625, 425]], ['control 6', {'initial_bp': 500, 'index_path': [700], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [1000]]], [['regression: cap reference rate', {'initial_bp': 300, 'index_path': [650, 250, 50, 537, 50], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [500, 500, 375, 575, 375]], ['control 1', {'initial_bp': 300, 'index_path': [400, 400, 537], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 675, 800]], ['control 2', {'initial_bp': 500, 'index_path': [537], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [700]], ['control 3', {'initial_bp': 300, 'index_path': [250, 250, 250], 'margin_bp': 250, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [500, 500, 500]], ['control 4', {'initial_bp': 500, 'index_path': [100, 212, 100], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [350, 450, 350]], ['control 5', {'initial_bp': 500, 'index_path': [100], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [400]], ['control 6', {'initial_bp': 500, 'index_path': [250, 650], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [525, 725]]], [['regression: cap reference rate', {'initial_bp': 300, 'index_path': [400, 537, 100], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [500, 700, 500]], ['control 1', {'initial_bp': 450, 'index_path': [650], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [875]], ['control 2', {'initial_bp': 500, 'index_path': [400, 212], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [650, 550]], ['control 3', {'initial_bp': 450, 'index_path': [400, 537], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [650, 775]], ['control 4', {'initial_bp': 450, 'index_path': [400, 50, 212, 250], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [675, 475, 475, 525]], ['control 5', {'initial_bp': 300, 'index_path': [250], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [500]], ['control 6', {'initial_bp': 300, 'index_path': [50, 50], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [400, 400]]]]
for label, args, expected in fixtures[N-1]:
    try:
        actual = solve(args)
    except Exception as exc:
        actual = 'raised ' + type(exc).__name__
    check(label, actual, 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: cap reference rate[500, 400, 400, 475, 600][500, 400, 400, 500, 600]Failed
regression: cap reference rate, partial-repair probe[475, 575, 775, 425, 875][475, 575, 475, 575, 675]Failed
control 1[875][875]Passed
control 2[475, 475][475, 475]Passed
control 3[400, 350, 550][400, 350, 550]Passed
control 4[300, 325][300, 325]Passed
control 5[700][700]Passed

SHA-256 / 942ac3fe71c1c822c4f3ec94f1907ae3986cb4194cb2c5fc7e66e847155977c7

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(x):
    rate = x['initial_bp']
    out = []
    life_max = x['initial_bp'] + x['lifetime_cap_bp']
    for i, idx in enumerate(x['index_path']):
        fi = idx + x['margin_bp']
        q, r = divmod(fi, x['round_to'])
        fi = (q + (1 if 2 * r >= x['round_to'] else 0)) * x['round_to']
        cap = x['initial_cap_bp'] if i == 0 else x['periodic_cap_bp']
        new = max(rate - cap, min(fi, rate + cap))
        new = max(x['floor_bp'], min(new, life_max))
        out.append(new)
        rate = x['initial_bp']
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression: cap reference rate', {'initial_bp': 500, 'index_path': [212, 100, 50, 250, 700], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 400, 400, 500, 600]], ['regression: cap reference rate, partial-repair probe', {'initial_bp': 450, 'index_path': [250, 650, 100, 650, 650], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [475, 575, 475, 575, 675]], ['control 1', {'initial_bp': 500, 'index_path': [650], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [875]], ['control 2', {'initial_bp': 300, 'index_path': [212, 212], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [475, 475]], ['control 3', {'initial_bp': 300, 'index_path': [100, 50, 250], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [400, 350, 550]], ['control 4', {'initial_bp': 450, 'index_path': [50, 100], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [300, 325]], ['control 5', {'initial_bp': 500, 'index_path': [700], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [700]]], [['regression: cap reference rate', {'initial_bp': 450, 'index_path': [650, 50, 212], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [650, 550, 500]], ['control 1', {'initial_bp': 500, 'index_path': [537, 650, 250, 400, 537], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [700, 875, 675, 625, 750]], ['control 2', {'initial_bp': 450, 'index_path': [250, 100, 700], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [475, 325, 525]], ['control 3', {'initial_bp': 450, 'index_path': [400, 700], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [625, 825]], ['control 4', {'initial_bp': 500, 'index_path': [212], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [375]], ['control 5', {'initial_bp': 300, 'index_path': [250], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [525]], ['control 6', {'initial_bp': 450, 'index_path': [50], 'margin_bp': 250, 'round_to': 50, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [400]]], [['regression: cap reference rate', {'initial_bp': 450, 'index_path': [212, 650, 50, 650], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [500, 700, 500, 700]], ['control 1', {'initial_bp': 450, 'index_path': [250, 250, 212], 'margin_bp': 225, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [500, 500, 450]], ['control 2', {'initial_bp': 450, 'index_path': [100], 'margin_bp': 225, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [400]], ['control 3', {'initial_bp': 500, 'index_path': [700, 250], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [1000, 900]], ['control 4', {'initial_bp': 500, 'index_path': [212, 537], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 700]], ['control 5', {'initial_bp': 450, 'index_path': [400, 50], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [625, 425]], ['control 6', {'initial_bp': 500, 'index_path': [700], 'margin_bp': 275, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [1000]]], [['regression: cap reference rate', {'initial_bp': 300, 'index_path': [650, 250, 50, 537, 50], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [500, 500, 375, 575, 375]], ['control 1', {'initial_bp': 300, 'index_path': [400, 400, 537], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [500, 675, 800]], ['control 2', {'initial_bp': 500, 'index_path': [537], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [700]], ['control 3', {'initial_bp': 300, 'index_path': [250, 250, 250], 'margin_bp': 250, 'round_to': 50, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [500, 500, 500]], ['control 4', {'initial_bp': 500, 'index_path': [100, 212, 100], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 225}, [350, 450, 350]], ['control 5', {'initial_bp': 500, 'index_path': [100], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [400]], ['control 6', {'initial_bp': 500, 'index_path': [250, 650], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [525, 725]]], [['regression: cap reference rate', {'initial_bp': 300, 'index_path': [400, 537, 100], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [500, 700, 500]], ['control 1', {'initial_bp': 450, 'index_path': [650], 'margin_bp': 275, 'round_to': 125, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 300}, [875]], ['control 2', {'initial_bp': 500, 'index_path': [400, 212], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 100, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [650, 550]], ['control 3', {'initial_bp': 450, 'index_path': [400, 537], 'margin_bp': 250, 'round_to': 25, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 400}, [650, 775]], ['control 4', {'initial_bp': 450, 'index_path': [400, 50, 212, 250], 'margin_bp': 275, 'round_to': 25, 'initial_cap_bp': 500, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 225}, [675, 475, 475, 525]], ['control 5', {'initial_bp': 300, 'index_path': [250], 'margin_bp': 225, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 600, 'floor_bp': 300}, [500]], ['control 6', {'initial_bp': 300, 'index_path': [50, 50], 'margin_bp': 250, 'round_to': 125, 'initial_cap_bp': 200, 'periodic_cap_bp': 200, 'lifetime_cap_bp': 500, 'floor_bp': 400}, [400, 400]]]]
for label, args, expected in fixtures[N-1]:
    try:
        actual = solve(args)
    except Exception as exc:
        actual = 'raised ' + type(exc).__name__
    check(label, actual, 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: cap reference rate[500, 400, 400, 500, 600][500, 400, 400, 500, 600]Passed
regression: cap reference rate, partial-repair probe[475, 550, 350, 550, 550][475, 575, 475, 575, 675]Failed
control 1[875][875]Passed
control 2[475, 475][475, 475]Passed
control 3[400, 350, 500][400, 350, 550]Failed
control 4[300, 325][300, 325]Passed
control 5[700][700]Passed

SHA-256 / 640995405420b2f4076215e40e0a4edb4b275471a4b3da3426f830f507883f22

HELD IN THE MEMBER ARCHIVE

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

This mechanism has 7 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.

Sign in to the archive ↗

Verification & scope

A deterministic bounded teaching model with stipulated toy lending rules stated in the contract; money is integer cents and rates are basis points; it makes no claim of conformance to any regulation, servicing standard or product. 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 2026-09-29T14:46:28.008979+00:00.

Case digest / 35a228a2e0e65711efcf524377e1e2798724799411244bdc9054f1028deec358