FA-9066 / Direct manipulation / Open access

Gesture axis locking and cancellation: Motion exactly at the activation threshold is ignored · case 01

Motion exactly at the activation threshold is ignored.

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

ROOT CAUSE

The threshold boundary operation uses `<= threshold` where the contract requires `< threshold`.

VERIFIED REPAIR

Implement the threshold boundary operation as `< threshold`.

Unsuccessful approach: Reversing the comparison activates small motion and suppresses large motion.

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 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	`[None, 0, 0]`	`['x', 5, 0]`	Failed
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 / 13e378300a6b518478ec46d08511fd7ab28f3fd30d796d64e2aa4322eecb2f1f

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 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	`[None, 0, 0]`	`['x', -10, 0]`	Failed
threshold	`['x', 5, 0]`	`['x', 5, 0]`	Passed
small	`['x', 2, 0]`	`[None, 0, 0]`	Failed
dominant negative	`[None, 0, 0]`	`['x', -10, 0]`	Failed
vertical	`[None, 0, 0]`	`['y', 0, -10]`	Failed
locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed
parameterized gesture distance	`[None, 0, 0]`	`['x', 2, 0]`	Failed
repeat locked	`['x', 2, 0]`	`['x', 2, 0]`	Passed

SHA-256 / 46d813ae4c5b5ee15317870c793081654fb11c376c6f8de848342cb04083e409

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 2026-09-29T14:38:26.812697+00:00.

Case digest / 65e20522578c2cf8090ca7cafb8bcf6106cc7a31d3b9af8bfb63b8dfbd6d6776