FAILURE MAP
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FA-87416 / Collision detection broadphase / Open access

Fat box size test uses half perimeter instead of area · case 01

The shrink rule triggers at the wrong sizes.

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

ROOT CAUSE

area() returns width+height.

VERIFIED REPAIR

Area is width*height.

Unsuccessful approach: Squaring the width ignores height.

Case contract

solve(tight, fat, disp, margin, mult): dynamic-tree proxy update. If the stored fat box contains the new tight box (inclusive) and its area is at most 4x that of a freshly built fat box, keep it: [False, fat]. Otherwise rebuild: tight expanded by margin on all sides, then extended by mult*disp on the side the motion points to; return [True, rebuilt box rounded to 6].

Why this case matters

Broadphase stages decide which object pairs ever reach narrowphase; a wrong boundary, ordering or bookkeeping rule silently drops real contacts or floods the solver with false candidates.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(tight, fat, disp, margin, mult):
    def fatten():
        f = [tight[0] - margin, tight[1] - margin, tight[2] + margin, tight[3] + margin]
        dx, dy = mult * disp[0], mult * disp[1]
        if dx < 0:
            f[0] += dx
        else:
            f[2] += dx
        if dy < 0:
            f[1] += dy
        else:
            f[3] += dy
        return [round(c, 6) for c in f]
    def area(b):
        return (b[2] - b[0]) + (b[3] - b[1])
    inside = fat[0] <= tight[0] and fat[1] <= tight[1] and tight[2] <= fat[2] and tight[3] <= fat[3]
    fresh = fatten()
    if inside and area(fat) <= 4 * area(fresh):
        return [False, fat]
    return [True, fresh]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[[-3.3, 2.7, -1.0, 3.3], [-3.4, 2.0, -0.3, 3.3], [-0.1, 0.1], 0.1, 1.0], [False, [-3.4, 2.0, -0.3, 3.3]]], [[[2.8, 1.5, 4.5, 2.1], [1.8, -1.5, 5.5, 3.1], [0, 0.2], 0.2, 1.0], [True, [2.6, 1.3, 4.7, 2.5]]], [[[-0.7, -1.6, 0.4, 0.6], [-3.8, -4.4, 0.8, 1.3], [0.1, -0.2], 0.5, 1.0], [False, [-3.8, -4.4, 0.8, 1.3]]], [[[1.1, 3.2, 3.9, 5.5], [-2.0, 2.2, 4.3, 8.0], [0.1, 0.5], 0.5, 2.0], [False, [-2.0, 2.2, 4.3, 8.0]]], [[[-2.1, 0.0, 0.0, 0.6], [-3.0, -3.1, 1.1, 1.5], [-0.1, 0.1], 0.5, 1.0], [False, [-3.0, -3.1, 1.1, 1.5]]], [[[-3.1, -3.3, -2.8, -1.4], [-5.1, -4.3, -0.8, 0.6], [-0.1, 0], 0.2, 1.0], [True, [-3.4, -3.5, -2.6, -1.2]]], [[[1.4, 2.3, 2.0, 5.3], [-1.5, 2.0, 2.6, 8.5], [-0.1, -0.2], 0.5, 4.0], [False, [-1.5, 2.0, 2.6, 8.5]]], [[[2.4, 1.1, 3.5, 2.9], [1.4, -1.9, 4.5, 3.9], [0.1, 0], 0.1, 1.0], [True, [2.3, 1.0, 3.7, 3.0]]]], [[[[4.1, 1.7, 4.6, 2.0], [3.8, 1.55, 4.9, 2.3], [0, 0], 0.1, 1.0], [False, [3.8, 1.55, 4.9, 2.3]]], [[[2.8, -0.7, 5.5, 2.0], [-0.3, -1.3, 8.4, 2.9], [0.1, 0.1], 0.5, 2.0], [False, [-0.3, -1.3, 8.4, 2.9]]], [[[-0.1, -4.2, 0.7, -2.8], [-2.1, -6.2, 2.7, -0.8], [0, 0], 0.1, 1.0], [True, [-0.2, -4.3, 0.8, -2.7]]], [[[2.1, 1.6, 2.8, 3.0], [1.5, -0.2, 3.4, 3.6], [0, 0], 0.1, 1.0], [True, [2.0, 1.5, 2.9, 3.1]]], [[[2.3, -1.1, 3.1, 1.6], [1.2, -2.8, 3.4, 1.3], [-0.1, 0.5], 0.2, 1.0], [True, [2.0, -1.3, 3.3, 2.3]]], [[[-2.0, 2.3, -1.0, 3.7], [-4.0, 1.3, 1.0, 5.7], [-0.1, 0], 0.1, 1.0], [True, [-2.2, 2.2, -0.9, 3.8]]], [[[1.7, 2.9, 3.1, 4.9], [-1.2, 2.9, 6.2, 6.9], [-0.1, -1.0], 0.5, 2.0], [False, [-1.2, 2.9, 6.2, 6.9]]], [[[4.7, -1.4, 7.7, -0.5], [4.2, -2.1, 7.9, -0.8], [-0.1, 0.5], 0.1, 1.0], [True, [4.5, -1.5, 7.8, 0.1]]]], [[[[3.7, -3.3, 4.2, -1.7], [2.7, -6.3, 5.2, -0.7], [-0.1, 0], 0.2, 1.0], [True, [3.4, -3.5, 4.4, -1.5]]], [[[3.4, 4.5, 4.9, 5.2], [2.8, 2.7, 5.5, 5.8], [0, 0.2], 0.1, 1.0], [True, [3.3, 4.4, 5.0, 5.5]]], [[[-2.2, 1.4, -1.4, 1.7], [-2.8, 0.8, -0.8, 2.3], [0.1, 0], 0.2, 1.0], [False, [-2.8, 0.8, -0.8, 2.3]]], [[[-0.6, 3.3, 0.2, 3.6], [-1.6, 2.3, 1.2, 4.6], [0.1, 0.2], 0.1, 1.0], [True, [-0.7, 3.2, 0.4, 3.9]]], [[[2.8, -2.1, 4.4, -0.1], [1.8, -5.1, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [2.7, -2.2, 4.6, 0.0]]], [[[-2.2, -4.2, -1.7, -3.8], [-2.8, -4.8, -1.1, -3.2], [0.1, 0.2], 0.1, 1.0], [True, [-2.3, -4.3, -1.5, -3.5]]], [[[-0.4, -4.2, 1.4, -2.3], [-1.4, -4.7, 2.4, -1.3], [0, 0], 0.2, 1.0], [False, [-1.4, -4.7, 2.4, -1.3]]], [[[2.7, 1.4, 3.6, 2.2], [2.1, 1.2, 4.2, 2.7], [0, 0.1], 0.1, 1.0], [False, [2.1, 1.2, 4.2, 2.7]]]], [[[[2.8, -3.9, 3.2, -2.7], [2.2, -4.5, 3.8, -2.1], [-0.1, 0], 0.2, 1.0], [False, [2.2, -4.5, 3.8, -2.1]]], [[[-4.3, -2.2, -3.8, -0.3], [-4.9, -2.8, -3.2, 0.3], [-0.1, 0.2], 0.1, 1.0], [False, [-4.9, -2.8, -3.2, 0.3]]], [[[-1.0, -3.3, 0.9, -2.4], [-3.0, -4.3, 2.9, -0.4], [0.1, 0], 0.1, 1.0], [True, [-1.1, -3.4, 1.1, -2.3]]], [[[-0.9, -2.7, 0.9, -2.0], [-3.8, -3.7, 2.0, 1.0], [-0.1, 0], 0.5, 4.0], [True, [-1.8, -3.2, 1.4, -1.5]]], [[[3.4, 3.7, 4.3, 4.3], [3.1, 2.8, 4.6, 4.6], [0.1, 0], 0.1, 1.0], [False, [3.1, 2.8, 4.6, 4.6]]], [[[2.8, 0.8, 3.4, 3.6], [2.2, 0.7, 3.6, 4.2], [0.4, 0], 0.1, 4.0], [False, [2.2, 0.7, 3.6, 4.2]]], [[[-4.3, 2.1, -3.3, 3.0], [-6.3, 1.1, -1.3, 5.0], [0.1, 0], 0.1, 1.0], [True, [-4.4, 2.0, -3.1, 3.1]]], [[[1.3, -0.6, 2.3, 2.4], [0.7, 0.2, 2.1, 3.8], [0.4, -1.0], 0.2, 1.0], [True, [1.1, -1.8, 2.9, 2.6]]]], [[[[4.7, -1.7, 5.8, -1.1], [3.2, -2.2, 5.8, -0.1], [1.0, 0], 0.5, 4.0], [False, [3.2, -2.2, 5.8, -0.1]]], [[[-0.5, -4.5, 0.3, -2.9], [-1.1, -6.3, 0.9, -2.3], [0, 0], 0.1, 1.0], [True, [-0.6, -4.6, 0.4, -2.8]]], [[[3.4, -0.9, 4.4, -0.1], [2.4, -3.9, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [3.3, -1.0, 4.6, 0.0]]], [[[-3.1, 2.9, -0.8, 4.5], [-5.5, 1.9, 2.8, 5.0], [-0.6, 0], 0.5, 1.0], [False, [-5.5, 1.9, 2.8, 5.0]]], [[[4.2, -2.1, 5.8, -1.3], [3.0, -3.3, 7.0, -0.9], [0, 0], 0.2, 2.0], [True, [4.0, -2.3, 6.0, -1.1]]], [[[1.1, -0.0, 1.6, 1.7], [-2.9, -4.0, 5.6, 5.7], [-0.1, 0.2], 0.2, 1.0], [True, [0.8, -0.2, 1.8, 2.1]]], [[[-1.1, -2.7, 0.3, -0.3], [-2.3, -1.9, -0.3, 0.9], [1.0, -1.0], 0.2, 1.0], [True, [-1.3, -3.9, 1.5, -0.1]]], [[[4.2, 3.7, 5.9, 4.3], [2.2, 1.7, 7.9, 6.3], [0.1, 0], 0.2, 1.0], [True, [4.0, 3.5, 6.2, 4.5]]]]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("case %d" % i, 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
case 0[False, [-3.4, 2.0, -0.3, 3.3]][False, [-3.4, 2.0, -0.3, 3.3]]Passed
case 1[False, [1.8, -1.5, 5.5, 3.1]][True, [2.6, 1.3, 4.7, 2.5]]Failed
case 2[False, [-3.8, -4.4, 0.8, 1.3]][False, [-3.8, -4.4, 0.8, 1.3]]Passed
case 3[False, [-2.0, 2.2, 4.3, 8.0]][False, [-2.0, 2.2, 4.3, 8.0]]Passed
case 4[False, [-3.0, -3.1, 1.1, 1.5]][False, [-3.0, -3.1, 1.1, 1.5]]Passed
case 5[False, [-5.1, -4.3, -0.8, 0.6]][True, [-3.4, -3.5, -2.6, -1.2]]Failed
case 6[False, [-1.5, 2.0, 2.6, 8.5]][False, [-1.5, 2.0, 2.6, 8.5]]Passed
case 7[False, [1.4, -1.9, 4.5, 3.9]][True, [2.3, 1.0, 3.7, 3.0]]Failed

SHA-256 / 157d996266b05ee5341ce6caf27da4444cd29b7460cac78602bc2f189fdf6190

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(tight, fat, disp, margin, mult):
    def fatten():
        f = [tight[0] - margin, tight[1] - margin, tight[2] + margin, tight[3] + margin]
        dx, dy = mult * disp[0], mult * disp[1]
        if dx < 0:
            f[0] += dx
        else:
            f[2] += dx
        if dy < 0:
            f[1] += dy
        else:
            f[3] += dy
        return [round(c, 6) for c in f]
    def area(b):
        return (b[2] - b[0]) * (b[2] - b[0])
    inside = fat[0] <= tight[0] and fat[1] <= tight[1] and tight[2] <= fat[2] and tight[3] <= fat[3]
    fresh = fatten()
    if inside and area(fat) <= 4 * area(fresh):
        return [False, fat]
    return [True, fresh]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[[-3.3, 2.7, -1.0, 3.3], [-3.4, 2.0, -0.3, 3.3], [-0.1, 0.1], 0.1, 1.0], [False, [-3.4, 2.0, -0.3, 3.3]]], [[[2.8, 1.5, 4.5, 2.1], [1.8, -1.5, 5.5, 3.1], [0, 0.2], 0.2, 1.0], [True, [2.6, 1.3, 4.7, 2.5]]], [[[-0.7, -1.6, 0.4, 0.6], [-3.8, -4.4, 0.8, 1.3], [0.1, -0.2], 0.5, 1.0], [False, [-3.8, -4.4, 0.8, 1.3]]], [[[1.1, 3.2, 3.9, 5.5], [-2.0, 2.2, 4.3, 8.0], [0.1, 0.5], 0.5, 2.0], [False, [-2.0, 2.2, 4.3, 8.0]]], [[[-2.1, 0.0, 0.0, 0.6], [-3.0, -3.1, 1.1, 1.5], [-0.1, 0.1], 0.5, 1.0], [False, [-3.0, -3.1, 1.1, 1.5]]], [[[-3.1, -3.3, -2.8, -1.4], [-5.1, -4.3, -0.8, 0.6], [-0.1, 0], 0.2, 1.0], [True, [-3.4, -3.5, -2.6, -1.2]]], [[[1.4, 2.3, 2.0, 5.3], [-1.5, 2.0, 2.6, 8.5], [-0.1, -0.2], 0.5, 4.0], [False, [-1.5, 2.0, 2.6, 8.5]]], [[[2.4, 1.1, 3.5, 2.9], [1.4, -1.9, 4.5, 3.9], [0.1, 0], 0.1, 1.0], [True, [2.3, 1.0, 3.7, 3.0]]]], [[[[4.1, 1.7, 4.6, 2.0], [3.8, 1.55, 4.9, 2.3], [0, 0], 0.1, 1.0], [False, [3.8, 1.55, 4.9, 2.3]]], [[[2.8, -0.7, 5.5, 2.0], [-0.3, -1.3, 8.4, 2.9], [0.1, 0.1], 0.5, 2.0], [False, [-0.3, -1.3, 8.4, 2.9]]], [[[-0.1, -4.2, 0.7, -2.8], [-2.1, -6.2, 2.7, -0.8], [0, 0], 0.1, 1.0], [True, [-0.2, -4.3, 0.8, -2.7]]], [[[2.1, 1.6, 2.8, 3.0], [1.5, -0.2, 3.4, 3.6], [0, 0], 0.1, 1.0], [True, [2.0, 1.5, 2.9, 3.1]]], [[[2.3, -1.1, 3.1, 1.6], [1.2, -2.8, 3.4, 1.3], [-0.1, 0.5], 0.2, 1.0], [True, [2.0, -1.3, 3.3, 2.3]]], [[[-2.0, 2.3, -1.0, 3.7], [-4.0, 1.3, 1.0, 5.7], [-0.1, 0], 0.1, 1.0], [True, [-2.2, 2.2, -0.9, 3.8]]], [[[1.7, 2.9, 3.1, 4.9], [-1.2, 2.9, 6.2, 6.9], [-0.1, -1.0], 0.5, 2.0], [False, [-1.2, 2.9, 6.2, 6.9]]], [[[4.7, -1.4, 7.7, -0.5], [4.2, -2.1, 7.9, -0.8], [-0.1, 0.5], 0.1, 1.0], [True, [4.5, -1.5, 7.8, 0.1]]]], [[[[3.7, -3.3, 4.2, -1.7], [2.7, -6.3, 5.2, -0.7], [-0.1, 0], 0.2, 1.0], [True, [3.4, -3.5, 4.4, -1.5]]], [[[3.4, 4.5, 4.9, 5.2], [2.8, 2.7, 5.5, 5.8], [0, 0.2], 0.1, 1.0], [True, [3.3, 4.4, 5.0, 5.5]]], [[[-2.2, 1.4, -1.4, 1.7], [-2.8, 0.8, -0.8, 2.3], [0.1, 0], 0.2, 1.0], [False, [-2.8, 0.8, -0.8, 2.3]]], [[[-0.6, 3.3, 0.2, 3.6], [-1.6, 2.3, 1.2, 4.6], [0.1, 0.2], 0.1, 1.0], [True, [-0.7, 3.2, 0.4, 3.9]]], [[[2.8, -2.1, 4.4, -0.1], [1.8, -5.1, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [2.7, -2.2, 4.6, 0.0]]], [[[-2.2, -4.2, -1.7, -3.8], [-2.8, -4.8, -1.1, -3.2], [0.1, 0.2], 0.1, 1.0], [True, [-2.3, -4.3, -1.5, -3.5]]], [[[-0.4, -4.2, 1.4, -2.3], [-1.4, -4.7, 2.4, -1.3], [0, 0], 0.2, 1.0], [False, [-1.4, -4.7, 2.4, -1.3]]], [[[2.7, 1.4, 3.6, 2.2], [2.1, 1.2, 4.2, 2.7], [0, 0.1], 0.1, 1.0], [False, [2.1, 1.2, 4.2, 2.7]]]], [[[[2.8, -3.9, 3.2, -2.7], [2.2, -4.5, 3.8, -2.1], [-0.1, 0], 0.2, 1.0], [False, [2.2, -4.5, 3.8, -2.1]]], [[[-4.3, -2.2, -3.8, -0.3], [-4.9, -2.8, -3.2, 0.3], [-0.1, 0.2], 0.1, 1.0], [False, [-4.9, -2.8, -3.2, 0.3]]], [[[-1.0, -3.3, 0.9, -2.4], [-3.0, -4.3, 2.9, -0.4], [0.1, 0], 0.1, 1.0], [True, [-1.1, -3.4, 1.1, -2.3]]], [[[-0.9, -2.7, 0.9, -2.0], [-3.8, -3.7, 2.0, 1.0], [-0.1, 0], 0.5, 4.0], [True, [-1.8, -3.2, 1.4, -1.5]]], [[[3.4, 3.7, 4.3, 4.3], [3.1, 2.8, 4.6, 4.6], [0.1, 0], 0.1, 1.0], [False, [3.1, 2.8, 4.6, 4.6]]], [[[2.8, 0.8, 3.4, 3.6], [2.2, 0.7, 3.6, 4.2], [0.4, 0], 0.1, 4.0], [False, [2.2, 0.7, 3.6, 4.2]]], [[[-4.3, 2.1, -3.3, 3.0], [-6.3, 1.1, -1.3, 5.0], [0.1, 0], 0.1, 1.0], [True, [-4.4, 2.0, -3.1, 3.1]]], [[[1.3, -0.6, 2.3, 2.4], [0.7, 0.2, 2.1, 3.8], [0.4, -1.0], 0.2, 1.0], [True, [1.1, -1.8, 2.9, 2.6]]]], [[[[4.7, -1.7, 5.8, -1.1], [3.2, -2.2, 5.8, -0.1], [1.0, 0], 0.5, 4.0], [False, [3.2, -2.2, 5.8, -0.1]]], [[[-0.5, -4.5, 0.3, -2.9], [-1.1, -6.3, 0.9, -2.3], [0, 0], 0.1, 1.0], [True, [-0.6, -4.6, 0.4, -2.8]]], [[[3.4, -0.9, 4.4, -0.1], [2.4, -3.9, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [3.3, -1.0, 4.6, 0.0]]], [[[-3.1, 2.9, -0.8, 4.5], [-5.5, 1.9, 2.8, 5.0], [-0.6, 0], 0.5, 1.0], [False, [-5.5, 1.9, 2.8, 5.0]]], [[[4.2, -2.1, 5.8, -1.3], [3.0, -3.3, 7.0, -0.9], [0, 0], 0.2, 2.0], [True, [4.0, -2.3, 6.0, -1.1]]], [[[1.1, -0.0, 1.6, 1.7], [-2.9, -4.0, 5.6, 5.7], [-0.1, 0.2], 0.2, 1.0], [True, [0.8, -0.2, 1.8, 2.1]]], [[[-1.1, -2.7, 0.3, -0.3], [-2.3, -1.9, -0.3, 0.9], [1.0, -1.0], 0.2, 1.0], [True, [-1.3, -3.9, 1.5, -0.1]]], [[[4.2, 3.7, 5.9, 4.3], [2.2, 1.7, 7.9, 6.3], [0.1, 0], 0.2, 1.0], [True, [4.0, 3.5, 6.2, 4.5]]]]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("case %d" % i, 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
case 0[False, [-3.4, 2.0, -0.3, 3.3]][False, [-3.4, 2.0, -0.3, 3.3]]Passed
case 1[False, [1.8, -1.5, 5.5, 3.1]][True, [2.6, 1.3, 4.7, 2.5]]Failed
case 2[True, [-1.2, -2.3, 1.0, 1.1]][False, [-3.8, -4.4, 0.8, 1.3]]Failed
case 3[False, [-2.0, 2.2, 4.3, 8.0]][False, [-2.0, 2.2, 4.3, 8.0]]Passed
case 4[False, [-3.0, -3.1, 1.1, 1.5]][False, [-3.0, -3.1, 1.1, 1.5]]Passed
case 5[True, [-3.4, -3.5, -2.6, -1.2]][True, [-3.4, -3.5, -2.6, -1.2]]Passed
case 6[True, [0.5, 1.0, 2.5, 5.8]][False, [-1.5, 2.0, 2.6, 8.5]]Failed
case 7[True, [2.3, 1.0, 3.7, 3.0]][True, [2.3, 1.0, 3.7, 3.0]]Passed

SHA-256 / a53b9ad9f9c1433b95a8142833d47932629dc5e9235ae5dbc14f465ced7dd35f

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(tight, fat, disp, margin, mult):
    def fatten():
        f = [tight[0] - margin, tight[1] - margin, tight[2] + margin, tight[3] + margin]
        dx, dy = mult * disp[0], mult * disp[1]
        if dx < 0:
            f[0] += dx
        else:
            f[2] += dx
        if dy < 0:
            f[1] += dy
        else:
            f[3] += dy
        return [round(c, 6) for c in f]
    def area(b):
        return (b[2] - b[0]) * (b[3] - b[1])
    inside = fat[0] <= tight[0] and fat[1] <= tight[1] and tight[2] <= fat[2] and tight[3] <= fat[3]
    fresh = fatten()
    if inside and area(fat) <= 4 * area(fresh):
        return [False, fat]
    return [True, fresh]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[[-3.3, 2.7, -1.0, 3.3], [-3.4, 2.0, -0.3, 3.3], [-0.1, 0.1], 0.1, 1.0], [False, [-3.4, 2.0, -0.3, 3.3]]], [[[2.8, 1.5, 4.5, 2.1], [1.8, -1.5, 5.5, 3.1], [0, 0.2], 0.2, 1.0], [True, [2.6, 1.3, 4.7, 2.5]]], [[[-0.7, -1.6, 0.4, 0.6], [-3.8, -4.4, 0.8, 1.3], [0.1, -0.2], 0.5, 1.0], [False, [-3.8, -4.4, 0.8, 1.3]]], [[[1.1, 3.2, 3.9, 5.5], [-2.0, 2.2, 4.3, 8.0], [0.1, 0.5], 0.5, 2.0], [False, [-2.0, 2.2, 4.3, 8.0]]], [[[-2.1, 0.0, 0.0, 0.6], [-3.0, -3.1, 1.1, 1.5], [-0.1, 0.1], 0.5, 1.0], [False, [-3.0, -3.1, 1.1, 1.5]]], [[[-3.1, -3.3, -2.8, -1.4], [-5.1, -4.3, -0.8, 0.6], [-0.1, 0], 0.2, 1.0], [True, [-3.4, -3.5, -2.6, -1.2]]], [[[1.4, 2.3, 2.0, 5.3], [-1.5, 2.0, 2.6, 8.5], [-0.1, -0.2], 0.5, 4.0], [False, [-1.5, 2.0, 2.6, 8.5]]], [[[2.4, 1.1, 3.5, 2.9], [1.4, -1.9, 4.5, 3.9], [0.1, 0], 0.1, 1.0], [True, [2.3, 1.0, 3.7, 3.0]]]], [[[[4.1, 1.7, 4.6, 2.0], [3.8, 1.55, 4.9, 2.3], [0, 0], 0.1, 1.0], [False, [3.8, 1.55, 4.9, 2.3]]], [[[2.8, -0.7, 5.5, 2.0], [-0.3, -1.3, 8.4, 2.9], [0.1, 0.1], 0.5, 2.0], [False, [-0.3, -1.3, 8.4, 2.9]]], [[[-0.1, -4.2, 0.7, -2.8], [-2.1, -6.2, 2.7, -0.8], [0, 0], 0.1, 1.0], [True, [-0.2, -4.3, 0.8, -2.7]]], [[[2.1, 1.6, 2.8, 3.0], [1.5, -0.2, 3.4, 3.6], [0, 0], 0.1, 1.0], [True, [2.0, 1.5, 2.9, 3.1]]], [[[2.3, -1.1, 3.1, 1.6], [1.2, -2.8, 3.4, 1.3], [-0.1, 0.5], 0.2, 1.0], [True, [2.0, -1.3, 3.3, 2.3]]], [[[-2.0, 2.3, -1.0, 3.7], [-4.0, 1.3, 1.0, 5.7], [-0.1, 0], 0.1, 1.0], [True, [-2.2, 2.2, -0.9, 3.8]]], [[[1.7, 2.9, 3.1, 4.9], [-1.2, 2.9, 6.2, 6.9], [-0.1, -1.0], 0.5, 2.0], [False, [-1.2, 2.9, 6.2, 6.9]]], [[[4.7, -1.4, 7.7, -0.5], [4.2, -2.1, 7.9, -0.8], [-0.1, 0.5], 0.1, 1.0], [True, [4.5, -1.5, 7.8, 0.1]]]], [[[[3.7, -3.3, 4.2, -1.7], [2.7, -6.3, 5.2, -0.7], [-0.1, 0], 0.2, 1.0], [True, [3.4, -3.5, 4.4, -1.5]]], [[[3.4, 4.5, 4.9, 5.2], [2.8, 2.7, 5.5, 5.8], [0, 0.2], 0.1, 1.0], [True, [3.3, 4.4, 5.0, 5.5]]], [[[-2.2, 1.4, -1.4, 1.7], [-2.8, 0.8, -0.8, 2.3], [0.1, 0], 0.2, 1.0], [False, [-2.8, 0.8, -0.8, 2.3]]], [[[-0.6, 3.3, 0.2, 3.6], [-1.6, 2.3, 1.2, 4.6], [0.1, 0.2], 0.1, 1.0], [True, [-0.7, 3.2, 0.4, 3.9]]], [[[2.8, -2.1, 4.4, -0.1], [1.8, -5.1, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [2.7, -2.2, 4.6, 0.0]]], [[[-2.2, -4.2, -1.7, -3.8], [-2.8, -4.8, -1.1, -3.2], [0.1, 0.2], 0.1, 1.0], [True, [-2.3, -4.3, -1.5, -3.5]]], [[[-0.4, -4.2, 1.4, -2.3], [-1.4, -4.7, 2.4, -1.3], [0, 0], 0.2, 1.0], [False, [-1.4, -4.7, 2.4, -1.3]]], [[[2.7, 1.4, 3.6, 2.2], [2.1, 1.2, 4.2, 2.7], [0, 0.1], 0.1, 1.0], [False, [2.1, 1.2, 4.2, 2.7]]]], [[[[2.8, -3.9, 3.2, -2.7], [2.2, -4.5, 3.8, -2.1], [-0.1, 0], 0.2, 1.0], [False, [2.2, -4.5, 3.8, -2.1]]], [[[-4.3, -2.2, -3.8, -0.3], [-4.9, -2.8, -3.2, 0.3], [-0.1, 0.2], 0.1, 1.0], [False, [-4.9, -2.8, -3.2, 0.3]]], [[[-1.0, -3.3, 0.9, -2.4], [-3.0, -4.3, 2.9, -0.4], [0.1, 0], 0.1, 1.0], [True, [-1.1, -3.4, 1.1, -2.3]]], [[[-0.9, -2.7, 0.9, -2.0], [-3.8, -3.7, 2.0, 1.0], [-0.1, 0], 0.5, 4.0], [True, [-1.8, -3.2, 1.4, -1.5]]], [[[3.4, 3.7, 4.3, 4.3], [3.1, 2.8, 4.6, 4.6], [0.1, 0], 0.1, 1.0], [False, [3.1, 2.8, 4.6, 4.6]]], [[[2.8, 0.8, 3.4, 3.6], [2.2, 0.7, 3.6, 4.2], [0.4, 0], 0.1, 4.0], [False, [2.2, 0.7, 3.6, 4.2]]], [[[-4.3, 2.1, -3.3, 3.0], [-6.3, 1.1, -1.3, 5.0], [0.1, 0], 0.1, 1.0], [True, [-4.4, 2.0, -3.1, 3.1]]], [[[1.3, -0.6, 2.3, 2.4], [0.7, 0.2, 2.1, 3.8], [0.4, -1.0], 0.2, 1.0], [True, [1.1, -1.8, 2.9, 2.6]]]], [[[[4.7, -1.7, 5.8, -1.1], [3.2, -2.2, 5.8, -0.1], [1.0, 0], 0.5, 4.0], [False, [3.2, -2.2, 5.8, -0.1]]], [[[-0.5, -4.5, 0.3, -2.9], [-1.1, -6.3, 0.9, -2.3], [0, 0], 0.1, 1.0], [True, [-0.6, -4.6, 0.4, -2.8]]], [[[3.4, -0.9, 4.4, -0.1], [2.4, -3.9, 5.4, 0.9], [0.1, 0], 0.1, 1.0], [True, [3.3, -1.0, 4.6, 0.0]]], [[[-3.1, 2.9, -0.8, 4.5], [-5.5, 1.9, 2.8, 5.0], [-0.6, 0], 0.5, 1.0], [False, [-5.5, 1.9, 2.8, 5.0]]], [[[4.2, -2.1, 5.8, -1.3], [3.0, -3.3, 7.0, -0.9], [0, 0], 0.2, 2.0], [True, [4.0, -2.3, 6.0, -1.1]]], [[[1.1, -0.0, 1.6, 1.7], [-2.9, -4.0, 5.6, 5.7], [-0.1, 0.2], 0.2, 1.0], [True, [0.8, -0.2, 1.8, 2.1]]], [[[-1.1, -2.7, 0.3, -0.3], [-2.3, -1.9, -0.3, 0.9], [1.0, -1.0], 0.2, 1.0], [True, [-1.3, -3.9, 1.5, -0.1]]], [[[4.2, 3.7, 5.9, 4.3], [2.2, 1.7, 7.9, 6.3], [0.1, 0], 0.2, 1.0], [True, [4.0, 3.5, 6.2, 4.5]]]]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("case %d" % i, 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
case 0[False, [-3.4, 2.0, -0.3, 3.3]][False, [-3.4, 2.0, -0.3, 3.3]]Passed
case 1[True, [2.6, 1.3, 4.7, 2.5]][True, [2.6, 1.3, 4.7, 2.5]]Passed
case 2[False, [-3.8, -4.4, 0.8, 1.3]][False, [-3.8, -4.4, 0.8, 1.3]]Passed
case 3[False, [-2.0, 2.2, 4.3, 8.0]][False, [-2.0, 2.2, 4.3, 8.0]]Passed
case 4[False, [-3.0, -3.1, 1.1, 1.5]][False, [-3.0, -3.1, 1.1, 1.5]]Passed
case 5[True, [-3.4, -3.5, -2.6, -1.2]][True, [-3.4, -3.5, -2.6, -1.2]]Passed
case 6[False, [-1.5, 2.0, 2.6, 8.5]][False, [-1.5, 2.0, 2.6, 8.5]]Passed
case 7[True, [2.3, 1.0, 3.7, 3.0]][True, [2.3, 1.0, 3.7, 3.0]]Passed

SHA-256 / a36393680e05f4eb68c77243628b5f2a9f2f0c66dce8aaafa1f45484304a2802

Verification & scope

A deterministic bounded teaching model with stipulated toy conventions; not a production physics engine or spatial index. 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 2026-09-29T14:50:58.603034+00:00.

Case digest / cf18dcd107ab2e225c81cc6108928e78edc7cc726bcb4d1fa425e6c5167ab29f