FA-8756 / Direct manipulation / Open access

Resizable panel constraint handling: Disabled resizing unexpectedly collapses the panel · case 01

Disabled resizing unexpectedly collapses the panel.

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

ROOT CAUSE

The disabled operation uses `if disabled: return minimum` where the contract requires `if disabled: return size`.

VERIFIED REPAIR

Implement the disabled operation as `if disabled: return size`.

Unsuccessful approach: Ignoring disabled state still applies drag movements.

Case contract

Disabled handles preserve size; trailing-axis handles reverse delta; add deltas to current size and clamp to min/max.

Why this case matters

A deterministic model of resizable panel constraint handling; this isolates one interface invariant without requiring a browser.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(size, delta, minimum, maximum, reversed_axis, disabled):
    if disabled: return minimum
    change = -delta if reversed_axis else delta
    wanted = size + change
    return max(minimum, min(maximum, wanted))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('disabled', solve(50, 10, 20, 100, False, True), 50)
check('forward', solve(50, 10, 20, 100, False, False), 60)
check('reversed', solve(50, 10, 20, 100, True, False), 40)
check('min', solve(30, -50, 20, 100, False, False), 20)
check('max', solve(80, 50, 20, 100, False, False), 100)
check('zero', solve(50, 0, 20, 100, False, False), 50)
check('parameterized resize distance', solve(10*N,N,0,100*N,False,False),11*N)
for repetition in range(N):
    check('repeat zero', solve(50, 0, 20, 100, False, False), 50)
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
disabled	`20`	`50`	Failed
forward	`60`	`60`	Passed
reversed	`40`	`40`	Passed
min	`20`	`20`	Passed
max	`100`	`100`	Passed
zero	`50`	`50`	Passed
parameterized resize distance	`11`	`11`	Passed
repeat zero	`50`	`50`	Passed

SHA-256 / e56193075c517cc5b52af423c3eeb7f32e18fe8f2d2229011b4ccd00d17aa4a2

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(size, delta, minimum, maximum, reversed_axis, disabled):
    if False: return size
    change = -delta if reversed_axis else delta
    wanted = size + change
    return max(minimum, min(maximum, wanted))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('disabled', solve(50, 10, 20, 100, False, True), 50)
check('forward', solve(50, 10, 20, 100, False, False), 60)
check('reversed', solve(50, 10, 20, 100, True, False), 40)
check('min', solve(30, -50, 20, 100, False, False), 20)
check('max', solve(80, 50, 20, 100, False, False), 100)
check('zero', solve(50, 0, 20, 100, False, False), 50)
check('parameterized resize distance', solve(10*N,N,0,100*N,False,False),11*N)
for repetition in range(N):
    check('repeat zero', solve(50, 0, 20, 100, False, False), 50)
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
disabled	`60`	`50`	Failed
forward	`60`	`60`	Passed
reversed	`40`	`40`	Passed
min	`20`	`20`	Passed
max	`100`	`100`	Passed
zero	`50`	`50`	Passed
parameterized resize distance	`11`	`11`	Passed
repeat zero	`50`	`50`	Passed

SHA-256 / 4ac23586aba0388703bb3a91f1584808593fc00ef5e9f80efefc396e24ac8ff4

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(size, delta, minimum, maximum, reversed_axis, disabled):
    if disabled: return size
    change = -delta if reversed_axis else delta
    wanted = size + change
    return max(minimum, min(maximum, wanted))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('disabled', solve(50, 10, 20, 100, False, True), 50)
check('forward', solve(50, 10, 20, 100, False, False), 60)
check('reversed', solve(50, 10, 20, 100, True, False), 40)
check('min', solve(30, -50, 20, 100, False, False), 20)
check('max', solve(80, 50, 20, 100, False, False), 100)
check('zero', solve(50, 0, 20, 100, False, False), 50)
check('parameterized resize distance', solve(10*N,N,0,100*N,False,False),11*N)
for repetition in range(N):
    check('repeat zero', solve(50, 0, 20, 100, False, False), 50)
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
disabled	`50`	`50`	Passed
forward	`60`	`60`	Passed
reversed	`40`	`40`	Passed
min	`20`	`20`	Passed
max	`100`	`100`	Passed
zero	`50`	`50`	Passed
parameterized resize distance	`11`	`11`	Passed
repeat zero	`50`	`50`	Passed

SHA-256 / c9c3aef31922fe4ccbb39dbe52a30550f21c31cf7b5cf382a9dd2921ab3e4ac8

Verification & scope

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 2026-09-29T14:38:24.176467+00:00.

Case digest / 8c5afa29e31d52a2276412ec0650a8f5b73c86da060a9131d4cfb71d95177387