FA-11221 / Media timeline seeking / Open access

Track timestamp offset applied once · case 01

Local track timestamps are mixed with the shared presentation timeline.

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

ROOT CAUSE

Local track timestamps are mixed with the shared presentation timeline.

VERIFIED REPAIR

Preserve the media contract: Map track-local timestamps to the shared presentation timeline by adding one signed track offset.

Unsuccessful approach: Applying the offset in both demux and presentation stages shifts the track twice.

Case contract

Map track-local timestamps to the shared presentation timeline by adding one signed track offset.

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(timestamps, offset):
    return list(timestamps)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([0, 2], 5)),[5, 7])
check('fixture 2',solve(*([5, 7], -5)),[0, 2])
check('fixture 3',solve(*([], 3)),[])
check('fixture 4',solve(*([0], 0)),[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
fixture 1	`[0, 2]`	`[5, 7]`	Failed
fixture 2	`[5, 7]`	`[0, 2]`	Failed
fixture 3	`[]`	`[]`	Passed
fixture 4	`[0]`	`[0]`	Passed

SHA-256 / e616a2e6ba861e77285d2178114d5fda3b65207e50d07429805fa834423d58a7

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(timestamps, offset):
    return [t+2*offset for t in timestamps]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([0, 2], 5)),[5, 7])
check('fixture 2',solve(*([5, 7], -5)),[0, 2])
check('fixture 3',solve(*([], 3)),[])
check('fixture 4',solve(*([0], 0)),[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
fixture 1	`[10, 12]`	`[5, 7]`	Failed
fixture 2	`[-5, -3]`	`[0, 2]`	Failed
fixture 3	`[]`	`[]`	Passed
fixture 4	`[0]`	`[0]`	Passed

SHA-256 / 902da9f57d4d2bf6af761f47345732ad608f33d2a846afeef1932f8eda9e5924

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(timestamps, offset):
    return [t+offset for t in timestamps]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([0, 2], 5)),[5, 7])
check('fixture 2',solve(*([5, 7], -5)),[0, 2])
check('fixture 3',solve(*([], 3)),[])
check('fixture 4',solve(*([0], 0)),[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
fixture 1	`[5, 7]`	`[5, 7]`	Passed
fixture 2	`[0, 2]`	`[0, 2]`	Passed
fixture 3	`[]`	`[]`	Passed
fixture 4	`[0]`	`[0]`	Passed

SHA-256 / e917d6414c577be18905b7e09a65b690327793f28fc6be85d6aade92d183ce59

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 2026-09-29T14:38:46.055626+00:00.

Case digest / 8e48669da303a334c8775f0d6449a71aef77838980b3a4439fa9b806a7af4dce