FA-36836 / Tab interfaces / Open access

Multirow tab strip: rowwise hit identity · case 01

The tab workspace reports an incorrect rowwise hit identity.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The rowwise hit identity decision uses list(range(len(x['widths']))) instead of [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].

VERIFIED REPAIR

Use the stipulated workspace rule: [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].

Unsuccessful approach: The partial repair list(reversed(range(len(x['widths'])))) 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 = (len(pack(x['widths'],x['available']))-1)*x['row_height']
    r5 = list(range(len(x['widths'])))
    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, [0, 1, 2, 3]]`	`[[[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]], 48, [0, 1, 2, 3]]`	`[[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]]`	Failed

SHA-256 / 7924759e06b64c85de2ac22afbb6ecdc662fc27d087297cab02642444db7df1c

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']))-1)*x['row_height']
    r5 = list(reversed(range(len(x['widths']))))
    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, [3, 2, 1, 0]]`	`[[[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]], 24, [3, 2, 1, 0]]`	`[[[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]], 24, [3, 2, 1, 0]]`	`[[[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, [3, 2, 1, 0]]`	`[[[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]], 0, [3, 2, 1, 0]]`	`[[[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]], 48, [3, 2, 1, 0]]`	`[[[0], [1, 2], [3]], 70, 1, [[0], [3], [1, 2]], 48, [0, 3, 1, 2]]`	Failed

SHA-256 / 42bc73b43223a0472ae6aa98334bcbef75ce083d724801e4119a25450e4576a9

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 2026-09-29T14:42:55.311092+00:00.

Case digest / 57c34ac70e1624cf24f127b8e264be5c7a9923966b94d365746afa9aac593567