FAILURE MAP
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FA-11071 / Media playlist state / Open access

Explicit skip bypasses repeat one · case 01

The natural-completion repeat-one rule traps an explicit skip on the same entry.

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

ROOT CAUSE

The natural-completion repeat-one rule traps an explicit skip on the same entry.

VERIFIED REPAIR

Preserve the media contract: An explicit user skip advances despite repeat-one; only repeat-all wraps at playlist end. Current is valid in nonempty playlist.

Unsuccessful approach: Wrapping every skip makes a nonrepeating playlist restart at the end.

Case contract

An explicit user skip advances despite repeat-one; only repeat-all wraps at playlist end. Current is valid in nonempty playlist.

Why this case matters

A deterministic local media controller stage; metadata and downloaded data are supplied explicitly. No external player, service or codec is required.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(current, length, repeat):
    return current if repeat=="one" else (current+1 if current+1<length else None)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(0, 3, 'one')),1)
check('fixture 2',solve(*(2, 3, 'one')),None)
check('fixture 3',solve(*(2, 3, 'all')),0)
check('fixture 4',solve(*(2, 3, 'off')),None)
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 101Failed
fixture 22NoneFailed
fixture 3None0Failed
fixture 4NoneNonePassed

SHA-256 / 4fd15ea7bf9080bb27865faafe5313ccda84067329a716db67d1d87b08c76b4c

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(current, length, repeat):
    return (current+1)%length
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(0, 3, 'one')),1)
check('fixture 2',solve(*(2, 3, 'one')),None)
check('fixture 3',solve(*(2, 3, 'all')),0)
check('fixture 4',solve(*(2, 3, 'off')),None)
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 111Passed
fixture 20NoneFailed
fixture 300Passed
fixture 40NoneFailed

SHA-256 / fe1fde18854562495ac5d3b3284d0bddc078fbb8b2e025b8c12b1f80897da458

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(current, length, repeat):
    return current+1 if current+1<length else (0 if repeat=="all" else None)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*(0, 3, 'one')),1)
check('fixture 2',solve(*(2, 3, 'one')),None)
check('fixture 3',solve(*(2, 3, 'all')),0)
check('fixture 4',solve(*(2, 3, 'off')),None)
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 111Passed
fixture 2NoneNonePassed
fixture 300Passed
fixture 4NoneNonePassed

SHA-256 / 27bc1fb9880db3d24f8a76cf518481570f0a2ab35925166ed8ede512b3683da8

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 2026-09-29T14:38:44.748809+00:00.

Case digest / 72900fdfa1eaa0a42abc11b9948be96ae2bdf9b156ea397bf7f87cbd3a0892e2