FAILURE MAP
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FA-10996 / Audio playback scheduling / Open access

Callback cancellation removes only target · case 01

Cancelling one scheduled sound clears unrelated scheduled work.

Verified by executionVariant 1 · 4 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Cancelling one scheduled sound clears unrelated scheduled work.

VERIFIED REPAIR

Apply the explicit PCM/playback contract: Pending events are [frame,cancellation token]. Cancel every event belonging to exactly the selected token, preserving others and their order.

Unsuccessful approach: Comparing the token against timestamp leaves matching work queued.

Case contract

Pending events are [frame,cancellation token]. Cancel every event belonging to exactly the selected token, preserving others and their order.

Why this case matters

A pure Python local audio pipeline stage with explicit sample formats and frame conventions; no real-time device or signal-spectrum claims.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(events, token):
    return []
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[4, 'a'], [5, 'b'], [6, 'a']], 'a')),[[5, 'b']])
check('fixture 2',solve(*([[4, 'a']], 'z')),[[4, 'a']])
check('fixture 3',solve(*([], 'a')),[])
check('fixture 4',solve(*([[4, 'a']], 'a')),[])
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 fixtureActualExpectedOutcome
fixture 1[][[5, 'b']]Failed
fixture 2[][[4, 'a']]Failed
fixture 3[][]Passed
fixture 4[][]Passed

SHA-256 / a42d874fb2474d3ae79beca462e3fcc2882134cb8ae5929acb071ef49a9b452c

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(events, token):
    return [x for x in events if x[0]!=token]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[4, 'a'], [5, 'b'], [6, 'a']], 'a')),[[5, 'b']])
check('fixture 2',solve(*([[4, 'a']], 'z')),[[4, 'a']])
check('fixture 3',solve(*([], 'a')),[])
check('fixture 4',solve(*([[4, 'a']], 'a')),[])
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 fixtureActualExpectedOutcome
fixture 1[[4, 'a'], [5, 'b'], [6, 'a']][[5, 'b']]Failed
fixture 2[[4, 'a']][[4, 'a']]Passed
fixture 3[][]Passed
fixture 4[[4, 'a']][]Failed

SHA-256 / b2a6abb778bf18d740b345d9caf00fb935332613632b518f61ecb576304abf42

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(events, token):
    return [x for x in events if x[1]!=token]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[4, 'a'], [5, 'b'], [6, 'a']], 'a')),[[5, 'b']])
check('fixture 2',solve(*([[4, 'a']], 'z')),[[4, 'a']])
check('fixture 3',solve(*([], 'a')),[])
check('fixture 4',solve(*([[4, 'a']], 'a')),[])
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 fixtureActualExpectedOutcome
fixture 1[[5, 'b']][[5, 'b']]Passed
fixture 2[[4, 'a']][[4, 'a']]Passed
fixture 3[][]Passed
fixture 4[][]Passed

SHA-256 / dd75a3c18ca382ef6184890d78fd64daadfb6ceaf56715794d9e80ee157c18c8

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 2026-09-29T14:38:44.092677+00:00.

Case digest / 61442143f74cae2a0ac987a0c6502b7c8936a21c42992efc2204f84dbc37d2f5