FA-8771 / Direct manipulation / Open access

Resizable panel constraint handling: Panels shrink below their minimum usable size · case 01

Panels shrink below their minimum usable size.

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

ROOT CAUSE

The minimum operation uses `min(maximum, wanted)` where the contract requires `max(minimum, min(maximum, wanted))`.

VERIFIED REPAIR

Implement the minimum operation as `max(minimum, min(maximum, wanted))`.

Unsuccessful approach: Using min turns the minimum into a ceiling.

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 size
    change = -delta if reversed_axis else delta
    wanted = size + change
    return 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`	Failed
max	`100`	`100`	Passed
zero	`50`	`50`	Passed
parameterized resize distance	`11`	`11`	Passed
repeat zero	`50`	`50`	Passed

SHA-256 / 799f1063e0e55b314161005318e88a670b477386e577f22e2b246a2cf9a57482

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 disabled: return size
    change = -delta if reversed_axis else delta
    wanted = size + change
    return min(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	`20`	`60`	Failed
reversed	`20`	`40`	Failed
min	`-20`	`20`	Failed
max	`20`	`100`	Failed
zero	`20`	`50`	Failed
parameterized resize distance	`0`	`11`	Failed
repeat zero	`20`	`50`	Failed

SHA-256 / 1609a3c0513fa040cc84f52d61f4dbae6fc1dc08531089d1d7ad9766656ad52c

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 2026-09-29T14:38:24.294372+00:00.

Case digest / 004ed3677d4b79fbe5af29063294e9124ea721a18348ad098f58da4971d1b921