FA-9076 / Direct manipulation / Open access

Gesture axis locking and cancellation: Established gesture locks switch axes mid-drag · case 01

Established gesture locks switch axes mid-drag.

Verified by executionVariant 1 · 9 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The persistent lock operation uses `if True:` where the contract requires `if locked is None:`.

VERIFIED REPAIR

Implement the persistent lock operation as `if locked is None:`.

Unsuccessful approach: Never choosing an axis sends fresh gestures to an arbitrary default.

Case contract

Cancelled gestures emit no movement; activate at the maximum absolute-axis threshold; choose dominant magnitude with horizontal tie; lock persists and suppresses cross-axis displacement.

Why this case matters

A deterministic model of gesture axis locking and cancellation; 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(dx, dy, threshold, locked, cancelled):
    if cancelled: return (None, 0, 0)
    if True:
        if max(abs(dx), abs(dy)) < threshold: return (None, 0, 0)
        locked = 'x' if abs(dx) >= abs(dy) else 'y'
    if locked == 'x': return ('x', dx, 0)
    return ('y', 0, dy)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('cancel', solve(10, 2, 5, 'x', True), (None, 0, 0))
check('negative', solve(-10, 0, 5, None, False), ('x', -10, 0))
check('threshold', solve(5, 0, 5, None, False), ('x', 5, 0))
check('small', solve(2, 1, 5, None, False), (None, 0, 0))
check('dominant negative', solve(-10, 3, 5, None, False), ('x', -10, 0))
check('vertical', solve(2, -10, 5, None, False), ('y', 0, -10))
check('locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
check('parameterized gesture distance', solve(2*N,0,N,None,False), ('x',2*N,0))
for repetition in range(N):
    check('repeat locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
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
cancel	`[None, 0, 0]`	`[None, 0, 0]`	Passed
negative	`['x', -10, 0]`	`['x', -10, 0]`	Passed
threshold	`['x', 5, 0]`	`['x', 5, 0]`	Passed
small	`[None, 0, 0]`	`[None, 0, 0]`	Passed
dominant negative	`['x', -10, 0]`	`['x', -10, 0]`	Passed
vertical	`['y', 0, -10]`	`['y', 0, -10]`	Passed
locked	`['y', 0, 20]`	`['x', 2, 0]`	Failed
parameterized gesture distance	`['x', 2, 0]`	`['x', 2, 0]`	Passed
repeat locked	`['y', 0, 20]`	`['x', 2, 0]`	Failed

SHA-256 / 48e41a908a4376f2a95de68ab80bad2f42107d43ca47cb606bc01097741dd4ca

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(dx, dy, threshold, locked, cancelled):
    if cancelled: return (None, 0, 0)
    if False:
        if max(abs(dx), abs(dy)) < threshold: return (None, 0, 0)
        locked = 'x' if abs(dx) >= abs(dy) else 'y'
    if locked == 'x': return ('x', dx, 0)
    return ('y', 0, dy)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('cancel', solve(10, 2, 5, 'x', True), (None, 0, 0))
check('negative', solve(-10, 0, 5, None, False), ('x', -10, 0))
check('threshold', solve(5, 0, 5, None, False), ('x', 5, 0))
check('small', solve(2, 1, 5, None, False), (None, 0, 0))
check('dominant negative', solve(-10, 3, 5, None, False), ('x', -10, 0))
check('vertical', solve(2, -10, 5, None, False), ('y', 0, -10))
check('locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
check('parameterized gesture distance', solve(2*N,0,N,None,False), ('x',2*N,0))
for repetition in range(N):
    check('repeat locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
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
cancel	`[None, 0, 0]`	`[None, 0, 0]`	Passed
negative	`['y', 0, 0]`	`['x', -10, 0]`	Failed
threshold	`['y', 0, 0]`	`['x', 5, 0]`	Failed
small	`['y', 0, 1]`	`[None, 0, 0]`	Failed
dominant negative	`['y', 0, 3]`	`['x', -10, 0]`	Failed
vertical	`['y', 0, -10]`	`['y', 0, -10]`	Passed
locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed
parameterized gesture distance	`['y', 0, 0]`	`['x', 2, 0]`	Failed
repeat locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed

SHA-256 / 3244f6678c997de6cba7e19a0aead3e979d40409d4c62d5da42b871680e0e427

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(dx, dy, threshold, locked, cancelled):
    if cancelled: return (None, 0, 0)
    if locked is None:
        if max(abs(dx), abs(dy)) < threshold: return (None, 0, 0)
        locked = 'x' if abs(dx) >= abs(dy) else 'y'
    if locked == 'x': return ('x', dx, 0)
    return ('y', 0, dy)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('cancel', solve(10, 2, 5, 'x', True), (None, 0, 0))
check('negative', solve(-10, 0, 5, None, False), ('x', -10, 0))
check('threshold', solve(5, 0, 5, None, False), ('x', 5, 0))
check('small', solve(2, 1, 5, None, False), (None, 0, 0))
check('dominant negative', solve(-10, 3, 5, None, False), ('x', -10, 0))
check('vertical', solve(2, -10, 5, None, False), ('y', 0, -10))
check('locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
check('parameterized gesture distance', solve(2*N,0,N,None,False), ('x',2*N,0))
for repetition in range(N):
    check('repeat locked', solve(2, 20, 5, "x", False), ('x', 2, 0))
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
cancel	`[None, 0, 0]`	`[None, 0, 0]`	Passed
negative	`['x', -10, 0]`	`['x', -10, 0]`	Passed
threshold	`['x', 5, 0]`	`['x', 5, 0]`	Passed
small	`[None, 0, 0]`	`[None, 0, 0]`	Passed
dominant negative	`['x', -10, 0]`	`['x', -10, 0]`	Passed
vertical	`['y', 0, -10]`	`['y', 0, -10]`	Passed
locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed
parameterized gesture distance	`['x', 2, 0]`	`['x', 2, 0]`	Passed
repeat locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed

SHA-256 / 1e950a9e1339eff02cbe4bfb5b7debe8996dd5657813e97b40aa53391dcbb184

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 2026-09-29T14:38:26.812641+00:00.

Case digest / 031c5f59d544cf757dd17f6d1c9f0d6ab9fe0d09e58f4f09abb053a669ca61c4