FA-36831 / Tab interfaces / Open access
Multirow tab strip: active row painted y · case 01
The tab workspace reports an incorrect active row painted y.
ROOT CAUSE
The active row painted y decision uses next(i for i,row in enumerate(pack(x['widths'],x['available'])) if x['active_index'] in row)*x['row_height'] instead of (len(pack(x['widths'],x['available']))-1)*x['row_height'].
VERIFIED REPAIR
Use the stipulated workspace rule: (len(pack(x['widths'],x['available']))-1)*x['row_height'].
Unsuccessful approach: The partial repair len(pack(x['widths'],x['available']))*x['row_height'] still violates a workspace boundary or normal case.
Case contract
A multirow strip greedily packs indivisible tab widths with exact fits allowed. The active tab row is painted adjacent to content after other rows; tab identity and within-row coordinates follow this row permutation.
Why this case matters
Offline tab/panel workspace behavior; no browser or desktop framework is emulated.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
def pack(widths, available):
rows = [[]]
occupied = 0
for index, width in enumerate(widths):
if rows[-1] and occupied + width > available:
rows.append([])
occupied = 0
rows[-1].append(index)
occupied += width
return rows
N = 1
observations = []
def solve(x):
r0 = pack(x['widths'],x['available'])
r1 = sum(x['widths'][j] for j in next(row for row in pack(x['widths'],x['available']) if x['active_index'] in row) if j<x['active_index'])
r2 = next(i for i,row in enumerate(pack(x['widths'],x['available'])) if x['active_index'] in row)
r3 = [row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]
r4 = next(i for i,row in enumerate(pack(x['widths'],x['available'])) if x['active_index'] in row)*x['row_height']
r5 = [t for row in ([row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]) for t in row]
return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 80, 50, 100], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 0, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 3, 'row_height': 24}, [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 300, 'active_index': 2, 'row_height': 24}, [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [100, 70, 70, 90], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]])], 2: [({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 160, 100, 200], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 0, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 48, [2, 3, 0, 1]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 3, 'row_height': 48}, [[[0, 1], [2, 3]], 180, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 600, 'active_index': 2, 'row_height': 48}, [[[0, 1, 2, 3]], 300, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [200, 140, 140, 180], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0], [1, 2], [3]], 140, 1, [[0], [3], [1, 2]], 96, [0, 3, 1, 2]])], 3: [({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 240, 150, 300], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 0, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 72, [2, 3, 0, 1]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 3, 'row_height': 72}, [[[0, 1], [2, 3]], 270, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 900, 'active_index': 2, 'row_height': 72}, [[[0, 1, 2, 3]], 450, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [300, 210, 210, 270], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0], [1, 2], [3]], 210, 1, [[0], [3], [1, 2]], 144, [0, 3, 1, 2]])], 4: [({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 320, 200, 400], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 0, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 96, [2, 3, 0, 1]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 3, 'row_height': 96}, [[[0, 1], [2, 3]], 360, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 1200, 'active_index': 2, 'row_height': 96}, [[[0, 1, 2, 3]], 600, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [400, 280, 280, 360], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0], [1, 2], [3]], 280, 1, [[0], [3], [1, 2]], 192, [0, 3, 1, 2]])], 5: [({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 400, 250, 500], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 0, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 120, [2, 3, 0, 1]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 3, 'row_height': 120}, [[[0, 1], [2, 3]], 450, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 1500, 'active_index': 2, 'row_height': 120}, [[[0, 1, 2, 3]], 750, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [500, 350, 350, 450], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0], [1, 2], [3]], 350, 1, [[0], [3], [1, 2]], 240, [0, 3, 1, 2]])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
check("workspace regression "+str(i), solve(inputs), 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 |
|---|---|---|---|
| workspace regression 0 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 1 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 2 | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 0, [2, 3, 0, 1]] | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]] | Failed |
| workspace regression 3 | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 4 | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]] | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]] | Passed |
| workspace regression 5 | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 24, [0, 3, 1, 2]] | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]] | Failed |
SHA-256 / f2960a9ba1ab92fddbe626e555ca8baffeba6254cda7bcf8260c7fd19027d331
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
def pack(widths, available):
rows = [[]]
occupied = 0
for index, width in enumerate(widths):
if rows[-1] and occupied + width > available:
rows.append([])
occupied = 0
rows[-1].append(index)
occupied += width
return rows
N = 1
observations = []
def solve(x):
r0 = pack(x['widths'],x['available'])
r1 = sum(x['widths'][j] for j in next(row for row in pack(x['widths'],x['available']) if x['active_index'] in row) if j<x['active_index'])
r2 = next(i for i,row in enumerate(pack(x['widths'],x['available'])) if x['active_index'] in row)
r3 = [row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]
r4 = len(pack(x['widths'],x['available']))*x['row_height']
r5 = [t for row in ([row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]) for t in row]
return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 80, 50, 100], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 0, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 3, 'row_height': 24}, [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 300, 'active_index': 2, 'row_height': 24}, [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [100, 70, 70, 90], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]])], 2: [({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 160, 100, 200], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 0, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 48, [2, 3, 0, 1]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 3, 'row_height': 48}, [[[0, 1], [2, 3]], 180, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 600, 'active_index': 2, 'row_height': 48}, [[[0, 1, 2, 3]], 300, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [200, 140, 140, 180], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0], [1, 2], [3]], 140, 1, [[0], [3], [1, 2]], 96, [0, 3, 1, 2]])], 3: [({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 240, 150, 300], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 0, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 72, [2, 3, 0, 1]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 3, 'row_height': 72}, [[[0, 1], [2, 3]], 270, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 900, 'active_index': 2, 'row_height': 72}, [[[0, 1, 2, 3]], 450, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [300, 210, 210, 270], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0], [1, 2], [3]], 210, 1, [[0], [3], [1, 2]], 144, [0, 3, 1, 2]])], 4: [({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 320, 200, 400], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 0, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 96, [2, 3, 0, 1]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 3, 'row_height': 96}, [[[0, 1], [2, 3]], 360, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 1200, 'active_index': 2, 'row_height': 96}, [[[0, 1, 2, 3]], 600, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [400, 280, 280, 360], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0], [1, 2], [3]], 280, 1, [[0], [3], [1, 2]], 192, [0, 3, 1, 2]])], 5: [({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 400, 250, 500], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 0, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 120, [2, 3, 0, 1]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 3, 'row_height': 120}, [[[0, 1], [2, 3]], 450, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 1500, 'active_index': 2, 'row_height': 120}, [[[0, 1, 2, 3]], 750, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [500, 350, 350, 450], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0], [1, 2], [3]], 350, 1, [[0], [3], [1, 2]], 240, [0, 3, 1, 2]])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
check("workspace regression "+str(i), solve(inputs), 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 |
|---|---|---|---|
| workspace regression 0 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Failed |
| workspace regression 1 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Failed |
| workspace regression 2 | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 48, [2, 3, 0, 1]] | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]] | Failed |
| workspace regression 3 | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Failed |
| workspace regression 4 | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]] | Failed |
| workspace regression 5 | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 72, [0, 3, 1, 2]] | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]] | Failed |
SHA-256 / 3a87ba706e3795575ff85278e03ed9aba78902a17b68497862ef9e2d554b46ca
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
def pack(widths, available):
rows = [[]]
occupied = 0
for index, width in enumerate(widths):
if rows[-1] and occupied + width > available:
rows.append([])
occupied = 0
rows[-1].append(index)
occupied += width
return rows
N = 1
observations = []
def solve(x):
r0 = pack(x['widths'],x['available'])
r1 = sum(x['widths'][j] for j in next(row for row in pack(x['widths'],x['available']) if x['active_index'] in row) if j<x['active_index'])
r2 = next(i for i,row in enumerate(pack(x['widths'],x['available'])) if x['active_index'] in row)
r3 = [row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]
r4 = (len(pack(x['widths'],x['available']))-1)*x['row_height']
r5 = [t for row in ([row for row in pack(x['widths'],x['available']) if x['active_index'] not in row]+[row for row in pack(x['widths'],x['available']) if x['active_index'] in row]) for t in row]
return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 80, 50, 100], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 0, 'row_height': 24}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]]), ({'widths': [80, 70, 90, 30], 'available': 160, 'active_index': 3, 'row_height': 24}, [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]]), ({'widths': [80, 70, 90, 30], 'available': 300, 'active_index': 2, 'row_height': 24}, [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [100, 70, 70, 90], 'available': 160, 'active_index': 2, 'row_height': 24}, [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]])], 2: [({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 160, 100, 200], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 0, 'row_height': 48}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 48, [2, 3, 0, 1]]), ({'widths': [160, 140, 180, 60], 'available': 320, 'active_index': 3, 'row_height': 48}, [[[0, 1], [2, 3]], 180, 1, [[0, 1], [2, 3]], 48, [0, 1, 2, 3]]), ({'widths': [160, 140, 180, 60], 'available': 600, 'active_index': 2, 'row_height': 48}, [[[0, 1, 2, 3]], 300, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [200, 140, 140, 180], 'available': 320, 'active_index': 2, 'row_height': 48}, [[[0], [1, 2], [3]], 140, 1, [[0], [3], [1, 2]], 96, [0, 3, 1, 2]])], 3: [({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 240, 150, 300], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 0, 'row_height': 72}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 72, [2, 3, 0, 1]]), ({'widths': [240, 210, 270, 90], 'available': 480, 'active_index': 3, 'row_height': 72}, [[[0, 1], [2, 3]], 270, 1, [[0, 1], [2, 3]], 72, [0, 1, 2, 3]]), ({'widths': [240, 210, 270, 90], 'available': 900, 'active_index': 2, 'row_height': 72}, [[[0, 1, 2, 3]], 450, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [300, 210, 210, 270], 'available': 480, 'active_index': 2, 'row_height': 72}, [[[0], [1, 2], [3]], 210, 1, [[0], [3], [1, 2]], 144, [0, 3, 1, 2]])], 4: [({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 320, 200, 400], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 0, 'row_height': 96}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 96, [2, 3, 0, 1]]), ({'widths': [320, 280, 360, 120], 'available': 640, 'active_index': 3, 'row_height': 96}, [[[0, 1], [2, 3]], 360, 1, [[0, 1], [2, 3]], 96, [0, 1, 2, 3]]), ({'widths': [320, 280, 360, 120], 'available': 1200, 'active_index': 2, 'row_height': 96}, [[[0, 1, 2, 3]], 600, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [400, 280, 280, 360], 'available': 640, 'active_index': 2, 'row_height': 96}, [[[0], [1, 2], [3]], 280, 1, [[0], [3], [1, 2]], 192, [0, 3, 1, 2]])], 5: [({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 400, 250, 500], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 0, 'row_height': 120}, [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 120, [2, 3, 0, 1]]), ({'widths': [400, 350, 450, 150], 'available': 800, 'active_index': 3, 'row_height': 120}, [[[0, 1], [2, 3]], 450, 1, [[0, 1], [2, 3]], 120, [0, 1, 2, 3]]), ({'widths': [400, 350, 450, 150], 'available': 1500, 'active_index': 2, 'row_height': 120}, [[[0, 1, 2, 3]], 750, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]]), ({'widths': [500, 350, 350, 450], 'available': 800, 'active_index': 2, 'row_height': 120}, [[[0], [1, 2], [3]], 350, 1, [[0], [3], [1, 2]], 240, [0, 3, 1, 2]])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
check("workspace regression "+str(i), solve(inputs), 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 |
|---|---|---|---|
| workspace regression 0 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 1 | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 0, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 2 | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]] | [[[0, 1], [2, 3]], 0, 0, [[2, 3], [0, 1]], 24, [2, 3, 0, 1]] | Passed |
| workspace regression 3 | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | [[[0, 1], [2, 3]], 90, 1, [[0, 1], [2, 3]], 24, [0, 1, 2, 3]] | Passed |
| workspace regression 4 | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]] | [[[0, 1, 2, 3]], 150, 0, [[0, 1, 2, 3]], 0, [0, 1, 2, 3]] | Passed |
| workspace regression 5 | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]] | [[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]] | Passed |
SHA-256 / 9a593670b8ce8623c719c9fc4b8fd544f2b8c146260e756f96bbeeba6fd41655
Verification & scope
Finite stipulated workspace snapshots only. Independent result fields describe observable obligations, not a full UI runtime. 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 2026-09-29T14:42:55.253344+00:00.
Case digest / 9913f46decf411c7b17778d73c2fc294a731c1d8c3f0eb61b2e898a5087253e7