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FA-78441 / Broadcast timecode arithmetic / Open access

Drop-frame label increment: frame carry · case 01

The label after ;29 is ;30 instead of the next second.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Frame carry only triggers above the nominal rate.

THE FAILURE

Frame carry only triggers above the nominal rate.

Unsuccessful approach: Carrying one frame early skips the last label of every second.

Case contract

Given a valid drop-frame label at rate "29.97" (nominal 30, drop 2) or "59.94" (nominal 60, drop 4), return the next label: frames carry into seconds at the nominal rate, seconds into minutes, minutes into hours (wrapping at 24); on entering a new minute not divisible by 10 the first drop labels are skipped.

Why this case matters

Timecode arithmetic errors misplace edits, commercial breaks and captions against the broadcast clock.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import re
N = 1
observations = []
def solve(tc, rate):
    n=30 if rate=='29.97' else 60
    drop=2 if n==30 else 4
    h,m,s,f=map(int,re.split('[:;]',tc))
    f+=1
    if f>n:
        f=0
        s+=1
        if s==60:
            s=0
            m+=1
            if m==60:
                m=0
                h=(h+1)%24
            if m%10!=0:
                f=drop
    return '%02d:%02d:%02d;%02d'%(h,m,s,f)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: frame carry', ['00:00:59;29', '29.97'], '00:01:00;02'), ('regression variant: frame carry', ['09:10:59;29', '29.97'], '09:11:00;02'), ('partial repair probe: frame carry', ['00:00:59;59', '59.94'], '00:01:00;04'), ('partial repair variant: frame carry', ['23:09:59;59', '59.94'], '23:10:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['01:01:01;02', '29.97'], '01:01:01;03'), ('normal control', ['01:00:01;00', '59.94'], '01:00:01;01'), ('normal control', ['01:00:59;02', '29.97'], '01:00:59;03')], [('regression: frame carry', ['00:09:59;29', '29.97'], '00:10:00;00'), ('regression variant: frame carry', ['09:00:59;29', '29.97'], '09:01:00;02'), ('partial repair probe: frame carry', ['23:59:59;29', '29.97'], '00:00:00;00'), ('partial repair variant: frame carry', ['09:19:59;58', '59.94'], '09:19:59;59'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['00:10:59;01', '59.94'], '00:10:59;02'), ('normal control', ['00:29:58;02', '59.94'], '00:29:58;03'), ('normal control', ['00:01:01;05', '59.94'], '00:01:01;06')], [('regression: frame carry', ['00:00:59;59', '59.94'], '00:01:00;04'), ('regression variant: frame carry', ['23:59:59;59', '59.94'], '00:00:00;00'), ('partial repair probe: frame carry', ['09:01:59;29', '29.97'], '09:02:00;02'), ('partial repair variant: frame carry', ['01:10:58;29', '29.97'], '01:10:59;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['23:29:01;15', '29.97'], '23:29:01;16'), ('normal control', ['00:09:01;00', '59.94'], '00:09:01;01'), ('normal control', ['01:10:58;15', '29.97'], '01:10:58;16')], [('regression: frame carry', ['23:59:59;29', '29.97'], '00:00:00;00'), ('regression variant: frame carry', ['23:09:59;59', '59.94'], '23:10:00;00'), ('partial repair probe: frame carry', ['09:10:59;29', '29.97'], '09:11:00;02'), ('partial repair variant: frame carry', ['23:09:59;29', '29.97'], '23:10:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['09:01:01;01', '29.97'], '09:01:01;02'), ('normal control', ['01:19:01;05', '59.94'], '01:19:01;06'), ('normal control', ['00:00:58;00', '29.97'], '00:00:58;01')], [('regression: frame carry', ['09:01:59;29', '29.97'], '09:02:00;02'), ('regression variant: frame carry', ['01:10:58;29', '29.97'], '01:10:59;00'), ('partial repair probe: frame carry', ['09:00:59;29', '29.97'], '09:01:00;02'), ('partial repair variant: frame carry', ['00:59:59;59', '59.94'], '01:00:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['01:09:01;04', '59.94'], '01:09:01;05'), ('normal control', ['09:09:01;02', '29.97'], '09:09:01;03'), ('normal control', ['00:01:59;02', '59.94'], '00:01:59;03')]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
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
regression: frame carry00:00:59;3000:01:00;02Failed
regression variant: frame carry09:10:59;3009:11:00;02Failed
partial repair probe: frame carry00:00:59;6000:01:00;04Failed
partial repair variant: frame carry23:09:59;6023:10:00;00Failed
boundary control00:01:00;0300:01:00;03Passed
normal control01:01:01;0301:01:01;03Passed
normal control01:00:01;0101:00:01;01Passed
normal control01:00:59;0301:00:59;03Passed

SHA-256 / 310fd0015ff1e110dab16f8b98335d24a738263131dbb0f4cfedb7c42a25f958

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import re
N = 1
observations = []
def solve(tc, rate):
    n=30 if rate=='29.97' else 60
    drop=2 if n==30 else 4
    h,m,s,f=map(int,re.split('[:;]',tc))
    f+=1
    if f==n-1:
        f=0
        s+=1
        if s==60:
            s=0
            m+=1
            if m==60:
                m=0
                h=(h+1)%24
            if m%10!=0:
                f=drop
    return '%02d:%02d:%02d;%02d'%(h,m,s,f)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: frame carry', ['00:00:59;29', '29.97'], '00:01:00;02'), ('regression variant: frame carry', ['09:10:59;29', '29.97'], '09:11:00;02'), ('partial repair probe: frame carry', ['00:00:59;59', '59.94'], '00:01:00;04'), ('partial repair variant: frame carry', ['23:09:59;59', '59.94'], '23:10:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['01:01:01;02', '29.97'], '01:01:01;03'), ('normal control', ['01:00:01;00', '59.94'], '01:00:01;01'), ('normal control', ['01:00:59;02', '29.97'], '01:00:59;03')], [('regression: frame carry', ['00:09:59;29', '29.97'], '00:10:00;00'), ('regression variant: frame carry', ['09:00:59;29', '29.97'], '09:01:00;02'), ('partial repair probe: frame carry', ['23:59:59;29', '29.97'], '00:00:00;00'), ('partial repair variant: frame carry', ['09:19:59;58', '59.94'], '09:19:59;59'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['00:10:59;01', '59.94'], '00:10:59;02'), ('normal control', ['00:29:58;02', '59.94'], '00:29:58;03'), ('normal control', ['00:01:01;05', '59.94'], '00:01:01;06')], [('regression: frame carry', ['00:00:59;59', '59.94'], '00:01:00;04'), ('regression variant: frame carry', ['23:59:59;59', '59.94'], '00:00:00;00'), ('partial repair probe: frame carry', ['09:01:59;29', '29.97'], '09:02:00;02'), ('partial repair variant: frame carry', ['01:10:58;29', '29.97'], '01:10:59;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['23:29:01;15', '29.97'], '23:29:01;16'), ('normal control', ['00:09:01;00', '59.94'], '00:09:01;01'), ('normal control', ['01:10:58;15', '29.97'], '01:10:58;16')], [('regression: frame carry', ['23:59:59;29', '29.97'], '00:00:00;00'), ('regression variant: frame carry', ['23:09:59;59', '59.94'], '23:10:00;00'), ('partial repair probe: frame carry', ['09:10:59;29', '29.97'], '09:11:00;02'), ('partial repair variant: frame carry', ['23:09:59;29', '29.97'], '23:10:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['09:01:01;01', '29.97'], '09:01:01;02'), ('normal control', ['01:19:01;05', '59.94'], '01:19:01;06'), ('normal control', ['00:00:58;00', '29.97'], '00:00:58;01')], [('regression: frame carry', ['09:01:59;29', '29.97'], '09:02:00;02'), ('regression variant: frame carry', ['01:10:58;29', '29.97'], '01:10:59;00'), ('partial repair probe: frame carry', ['09:00:59;29', '29.97'], '09:01:00;02'), ('partial repair variant: frame carry', ['00:59:59;59', '59.94'], '01:00:00;00'), ('boundary control', ['00:01:00;02', '29.97'], '00:01:00;03'), ('normal control', ['01:09:01;04', '59.94'], '01:09:01;05'), ('normal control', ['09:09:01;02', '29.97'], '09:09:01;03'), ('normal control', ['00:01:59;02', '59.94'], '00:01:59;03')]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
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
regression: frame carry00:00:59;3000:01:00;02Failed
regression variant: frame carry09:10:59;3009:11:00;02Failed
partial repair probe: frame carry00:00:59;6000:01:00;04Failed
partial repair variant: frame carry23:09:59;6023:10:00;00Failed
boundary control00:01:00;0300:01:00;03Passed
normal control01:01:01;0301:01:01;03Passed
normal control01:00:01;0101:00:01;01Passed
normal control01:00:59;0301:00:59;03Passed

SHA-256 / ea564b951ac1cebb378773cebe5b1af566cf4ce1623be3004bf4ab5ce824875c

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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Verification & scope

A deterministic bounded teaching model with a stipulated toy contract; it does not claim conformance to SMPTE or any broadcast standard. 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 2026-09-29T14:49:35.316242+00:00.

Case digest / 6304f0cb8021b991fbdb07d22ec266ea87e9eba195ca7e2fa3987bd8a7ea92f2