FAILURE MAP
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FA-70551 / GIS polygon topology / Open access

Hole placement validation against shell and siblings: nesting criterion · case 01

Duplicate or edge-sharing holes are reported as nested.

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

ROOT CAUSE

Nesting only requires all vertices inside-or-on the other hole, so a hole identical to its sibling counts as nested.

THE FAILURE

Nesting only requires all vertices inside-or-on the other hole, so a hole identical to its sibling counts as nested.

Unsuccessful approach: Requiring just one strictly inside vertex flags partially overlapping holes as nested.

Case contract

Input [shell, holes], closed integer rings. Point classification against a ring: on an edge = 0, inside by half-open crossing number = 1, else -1. For each hole in order: "outside" if any hole vertex is strictly outside the shell; else "coincident" if every hole vertex lies on the shell boundary; else "nested" if for some OTHER hole all its vertices are inside-or-on that hole and at least one is strictly inside; else "ok". Return one label per hole.

Why this case matters

Polygon validity rules require holes to lie inside the shell and not inside each other; mislabelled holes block valid data or let invalid parcels through.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
    shell, holes = x
    def cls(pt, ring):
        px, py = pt
        for a, b in zip(ring, ring[1:]):
            if (b[0] - a[0]) * (py - a[1]) - (b[1] - a[1]) * (px - a[0]) == 0 and min(a[0], b[0]) <= px <= max(a[0], b[0]) and min(a[1], b[1]) <= py <= max(a[1], b[1]):
                return 0
        c = False
        for a, b in zip(ring, ring[1:]):
            if (a[1] > py) != (b[1] > py) and px < a[0] + (py - a[1]) * (b[0] - a[0]) / (b[1] - a[1]):
                c = not c
        return 1 if c else -1
    out = []
    for i, h in enumerate(holes):
        vs = h[:-1]
        if any(cls(p, shell) < 0 for p in vs):
            out.append('outside')
            continue
        if all(cls(p, shell) == 0 for p in vs):
            out.append('coincident')
            continue
        nested = False
        for j, g in enumerate(holes):
            if j != i and all(cls(p, g) >= 0 for p in vs):
                nested = True
        out.append('nested' if nested else 'ok')
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['ok']), ('control #1', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]], [[8, 8], [8, 12], [12, 12], [12, 8], [8, 8]]]], ['ok', 'ok']), ('regression #2', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 5], [0, 9], [4, 9], [4, 5], [0, 5]]]], ['ok']), ('regression #3', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[18, 18], [18, 25], [25, 25], [25, 18], [18, 18]]]], ['outside']), ('regression #4', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [30, 10], [5, 15], [5, 5]]]], ['outside']), ('regression #5', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[25, 10], [10, 5], [10, 15], [25, 10]]]], ['outside']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok'])], [('regression #3', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[18, 18], [18, 25], [25, 25], [25, 18], [18, 18]]]], ['outside']), ('regression #4', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [30, 10], [5, 15], [5, 5]]]], ['outside']), ('regression #5', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[25, 10], [10, 5], [10, 15], [25, 10]]]], ['outside']), ('regression #6', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]]]], ['ok', 'nested']), ('regression #7', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]], [[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[14, 2], [14, 5], [18, 5], [18, 2], [14, 2]]]], ['nested', 'ok', 'ok']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #10', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [0, 20], [20, 20], [20, 0], [0, 0]]]], ['coincident'])], [('regression #6', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]]]], ['ok', 'nested']), ('regression #7', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]], [[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[14, 2], [14, 5], [18, 5], [18, 2], [14, 2]]]], ['nested', 'ok', 'ok']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #10', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [0, 20], [20, 20], [20, 0], [0, 0]]]], ['coincident']), ('boundary #11', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 0], [0, 5], [0, 0]]]], ['coincident']), ('boundary #12', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 3], [3, 5], [0, 0]]]], ['ok']), ('regression #13', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[22, 2], [22, 5], [25, 5], [25, 2], [22, 2]], [[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['outside', 'ok'])], [('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #11', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 0], [0, 5], [0, 0]]]], ['coincident']), ('boundary #12', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 3], [3, 5], [0, 0]]]], ['ok']), ('regression #13', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[22, 2], [22, 5], [25, 5], [25, 2], [22, 2]], [[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['outside', 'ok']), ('regression #14', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[-5, 2], [-5, 5], [3, 5], [3, 2], [-5, 2]], [[5, 5], [5, 9], [9, 9], [9, 5], [5, 5]], [[6, 6], [6, 7], [7, 7], [7, 6], [6, 6]]]], ['outside', 'ok', 'nested']), ('control #15', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 8], [8, 4]]]], ['ok']), ('regression #16', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 25], [8, 4]]]], ['outside'])], [('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('regression #14', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[-5, 2], [-5, 5], [3, 5], [3, 2], [-5, 2]], [[5, 5], [5, 9], [9, 9], [9, 5], [5, 5]], [[6, 6], [6, 7], [7, 7], [7, 6], [6, 6]]]], ['outside', 'ok', 'nested']), ('control #15', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 8], [8, 4]]]], ['ok']), ('regression #16', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 25], [8, 4]]]], ['outside']), ('boundary #17', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 6], [6, 6], [6, 2], [2, 2]], [[6, 2], [6, 6], [10, 6], [10, 2], [6, 2]]]], ['ok', 'ok']), ('control #18', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], []], []), ('regression #19', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]], [[5, 5], [5, 8], [8, 8], [8, 5], [5, 5]]]], ['ok', 'nested'])]]
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 fixtureActualExpectedOutcome
control #0['ok']['ok']Passed
control #1['ok', 'ok']['ok', 'ok']Passed
regression #2['ok']['ok']Passed
regression #3['outside']['outside']Passed
regression #4['outside']['outside']Passed
regression #5['outside']['outside']Passed
regression #8['ok', 'ok']['ok', 'ok']Passed
boundary #9['nested', 'nested']['ok', 'ok']Failed

SHA-256 / c83c8bb58966c7403710fe560c20527ae366398fac8abf1f6971985d5e743cf2

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
    shell, holes = x
    def cls(pt, ring):
        px, py = pt
        for a, b in zip(ring, ring[1:]):
            if (b[0] - a[0]) * (py - a[1]) - (b[1] - a[1]) * (px - a[0]) == 0 and min(a[0], b[0]) <= px <= max(a[0], b[0]) and min(a[1], b[1]) <= py <= max(a[1], b[1]):
                return 0
        c = False
        for a, b in zip(ring, ring[1:]):
            if (a[1] > py) != (b[1] > py) and px < a[0] + (py - a[1]) * (b[0] - a[0]) / (b[1] - a[1]):
                c = not c
        return 1 if c else -1
    out = []
    for i, h in enumerate(holes):
        vs = h[:-1]
        if any(cls(p, shell) < 0 for p in vs):
            out.append('outside')
            continue
        if all(cls(p, shell) == 0 for p in vs):
            out.append('coincident')
            continue
        nested = False
        for j, g in enumerate(holes):
            if j != i and any(cls(p, g) > 0 for p in vs):
                nested = True
        out.append('nested' if nested else 'ok')
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['ok']), ('control #1', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]], [[8, 8], [8, 12], [12, 12], [12, 8], [8, 8]]]], ['ok', 'ok']), ('regression #2', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 5], [0, 9], [4, 9], [4, 5], [0, 5]]]], ['ok']), ('regression #3', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[18, 18], [18, 25], [25, 25], [25, 18], [18, 18]]]], ['outside']), ('regression #4', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [30, 10], [5, 15], [5, 5]]]], ['outside']), ('regression #5', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[25, 10], [10, 5], [10, 15], [25, 10]]]], ['outside']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok'])], [('regression #3', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[18, 18], [18, 25], [25, 25], [25, 18], [18, 18]]]], ['outside']), ('regression #4', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [30, 10], [5, 15], [5, 5]]]], ['outside']), ('regression #5', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[25, 10], [10, 5], [10, 15], [25, 10]]]], ['outside']), ('regression #6', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]]]], ['ok', 'nested']), ('regression #7', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]], [[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[14, 2], [14, 5], [18, 5], [18, 2], [14, 2]]]], ['nested', 'ok', 'ok']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #10', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [0, 20], [20, 20], [20, 0], [0, 0]]]], ['coincident'])], [('regression #6', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]]]], ['ok', 'nested']), ('regression #7', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[4, 4], [4, 6], [6, 6], [6, 4], [4, 4]], [[2, 2], [2, 12], [12, 12], [12, 2], [2, 2]], [[14, 2], [14, 5], [18, 5], [18, 2], [14, 2]]]], ['nested', 'ok', 'ok']), ('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #10', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [0, 20], [20, 20], [20, 0], [0, 0]]]], ['coincident']), ('boundary #11', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 0], [0, 5], [0, 0]]]], ['coincident']), ('boundary #12', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 3], [3, 5], [0, 0]]]], ['ok']), ('regression #13', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[22, 2], [22, 5], [25, 5], [25, 2], [22, 2]], [[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['outside', 'ok'])], [('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('boundary #11', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 0], [0, 5], [0, 0]]]], ['coincident']), ('boundary #12', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[0, 0], [5, 3], [3, 5], [0, 0]]]], ['ok']), ('regression #13', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[22, 2], [22, 5], [25, 5], [25, 2], [22, 2]], [[2, 2], [2, 5], [5, 5], [5, 2], [2, 2]]]], ['outside', 'ok']), ('regression #14', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[-5, 2], [-5, 5], [3, 5], [3, 2], [-5, 2]], [[5, 5], [5, 9], [9, 9], [9, 5], [5, 5]], [[6, 6], [6, 7], [7, 7], [7, 6], [6, 6]]]], ['outside', 'ok', 'nested']), ('control #15', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 8], [8, 4]]]], ['ok']), ('regression #16', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 25], [8, 4]]]], ['outside'])], [('regression #8', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[6, 6], [6, 12], [12, 12], [12, 6], [6, 6]]]], ['ok', 'ok']), ('boundary #9', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]], [[2, 2], [2, 8], [8, 8], [8, 2], [2, 2]]]], ['ok', 'ok']), ('regression #14', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[-5, 2], [-5, 5], [3, 5], [3, 2], [-5, 2]], [[5, 5], [5, 9], [9, 9], [9, 5], [5, 5]], [[6, 6], [6, 7], [7, 7], [7, 6], [6, 6]]]], ['outside', 'ok', 'nested']), ('control #15', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 8], [8, 4]]]], ['ok']), ('regression #16', [[[0, 0], [20, 0], [10, 20], [0, 0]], [[[8, 4], [12, 4], [10, 25], [8, 4]]]], ['outside']), ('boundary #17', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[2, 2], [2, 6], [6, 6], [6, 2], [2, 2]], [[6, 2], [6, 6], [10, 6], [10, 2], [6, 2]]]], ['ok', 'ok']), ('control #18', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], []], []), ('regression #19', [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]], [[5, 5], [5, 8], [8, 8], [8, 5], [5, 5]]]], ['ok', 'nested'])]]
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 fixtureActualExpectedOutcome
control #0['ok']['ok']Passed
control #1['ok', 'ok']['ok', 'ok']Passed
regression #2['ok']['ok']Passed
regression #3['outside']['outside']Passed
regression #4['outside']['outside']Passed
regression #5['outside']['outside']Passed
regression #8['nested', 'nested']['ok', 'ok']Failed
boundary #9['ok', 'ok']['ok', 'ok']Passed

SHA-256 / dbb057865206367bda9f4b5336651628aedb2aa608ee1ddcbec325ebb077fa91

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.

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Verification & scope

Stipulated deterministic toy contract on a bounded input domain; results are rounded as stated and no conformance with any published standard or library is claimed. 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 2026-09-29T14:48:21.754799+00:00.

Case digest / 8886a9e297bad106b5ecfc681b3f7bac46f5c40303cfe231e0c4796793dc7899