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FA-78736 / Broadcast timecode arithmetic / Open access

Playout schedule on-air times: span operand order · case 01

Clip lengths come out as the complement of the real length.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The span subtracts EOM from SOM.

VERIFIED REPAIR

Span is EOM minus SOM.

Unsuccessful approach: Subtracting the schedule start instead of SOM confuses tape and air timelines.

Case contract

Clips [SOM, EOM] use non-drop labels at fps with EOM inclusive; a clip may cross midnight on tape. Clips air back to back from start with gap black frames between consecutive clips. Return the on-air label of each clip followed by the exclusive end label of the schedule, wrapping at 24 hours.

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

N = 1
observations = []
def solve(start, clips, gap, fps):
    def fr(t):
        h,m,s,f=map(int,t.split(':'))
        return ((h*60+m)*60+s)*fps+f
    def lab(n):
        n%=86400*fps
        return '%02d:%02d:%02d:%02d'%(n//(3600*fps),n//(60*fps)%60,n//fps%60,n%fps)
    t=fr(start)
    out=[]
    for i,(som,eom) in enumerate(clips):
        if i:
            t+=gap
        out.append(lab(t))
        d=(fr(som)-fr(eom))%(86400*fps)
        t+=d+1
    out.append(lab(t))
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: span operand order', ['18:00:00:00', [['10:00:00:00', '10:00:00:24']], 0, 25], ['18:00:00:00', '18:00:01:00']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 30], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 25, 30], ['23:59:50:00'])], [('regression: span operand order', ['23:59:59:00', [['00:00:00:00', '00:00:01:00'], ['00:00:00:00', '00:00:00:00']], 5, 25], ['23:59:59:00', '00:00:00:06', '00:00:00:07']), ('regression variant: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair probe: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['00:00:00:00', '00:00:00:10'], ['10:00:00:00', '01:00:30:00'], ['10:00:00:00', '00:00:01:00'], ['00:00:00:00', '10:00:29:24']], 0, 25], ['00:00:00:00', '00:00:00:11', '15:00:30:12', '05:00:31:13', '15:01:01:13']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 1, 25], ['23:59:50:00']), ('normal control', ['00:00:00:00', [], 25, 30], ['00:00:00:00'])], [('regression: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('regression variant: span operand order', ['18:00:00:00', [['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '10:00:10:00']], 0, 30], ['18:00:00:00', '04:00:29:25', '14:00:39:26']), ('partial repair probe: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['23:59:59:00', '00:00:01:00']], 5, 25], ['18:00:00:00', '18:00:01:16', '18:00:03:17']), ('normal control', ['18:00:00:00', [], 1, 25], ['18:00:00:00']), ('normal control', ['00:00:00:00', [], 0, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 25], ['00:00:00:00'])], [('regression: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '01:00:30:00'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '15:00:20:26', '16:00:50:27']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['10:00:00:00', '00:00:01:00'], ['10:00:00:00', '00:00:00:10']], 1, 30], ['00:00:00:00', '14:00:01:02', '04:00:01:13']), ('normal control', ['00:00:00:00', [], 0, 30], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 1, 30], ['23:59:50:00'])], [('regression: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('regression variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('partial repair probe: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 5, 25], ['23:59:50:00', '13:59:50:01']), ('normal control', ['23:59:50:00', [], 0, 25], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['18:00:00:00', [], 25, 30], ['18:00:00:00'])]]
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: span operand order['18:00:00:00', '17:59:59:02']['18:00:00:00', '18:00:01:00']Failed
regression variant: span operand order['23:59:50:00', '09:59:50:01']['23:59:50:00', '13:59:50:01']Failed
partial repair probe: span operand order['23:59:50:00', '09:59:50:16', '23:59:21:18', '22:58:51:19']['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']Failed
partial repair variant: span operand order['18:00:00:00', '17:59:58:16', '07:59:48:17', '07:59:48:18', '22:59:18:20']['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']Failed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['23:59:50:00']['23:59:50:00']Passed

SHA-256 / df3e8ae773e3e91f24ab87d7bedd5b1c30ed36dfc117bb765d851d84da742d5f

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(start, clips, gap, fps):
    def fr(t):
        h,m,s,f=map(int,t.split(':'))
        return ((h*60+m)*60+s)*fps+f
    def lab(n):
        n%=86400*fps
        return '%02d:%02d:%02d:%02d'%(n//(3600*fps),n//(60*fps)%60,n//fps%60,n%fps)
    t=fr(start)
    out=[]
    for i,(som,eom) in enumerate(clips):
        if i:
            t+=gap
        out.append(lab(t))
        d=(fr(eom)-fr(start))%(86400*fps)
        t+=d+1
    out.append(lab(t))
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: span operand order', ['18:00:00:00', [['10:00:00:00', '10:00:00:24']], 0, 25], ['18:00:00:00', '18:00:01:00']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 30], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 25, 30], ['23:59:50:00'])], [('regression: span operand order', ['23:59:59:00', [['00:00:00:00', '00:00:01:00'], ['00:00:00:00', '00:00:00:00']], 5, 25], ['23:59:59:00', '00:00:00:06', '00:00:00:07']), ('regression variant: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair probe: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['00:00:00:00', '00:00:00:10'], ['10:00:00:00', '01:00:30:00'], ['10:00:00:00', '00:00:01:00'], ['00:00:00:00', '10:00:29:24']], 0, 25], ['00:00:00:00', '00:00:00:11', '15:00:30:12', '05:00:31:13', '15:01:01:13']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 1, 25], ['23:59:50:00']), ('normal control', ['00:00:00:00', [], 25, 30], ['00:00:00:00'])], [('regression: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('regression variant: span operand order', ['18:00:00:00', [['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '10:00:10:00']], 0, 30], ['18:00:00:00', '04:00:29:25', '14:00:39:26']), ('partial repair probe: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['23:59:59:00', '00:00:01:00']], 5, 25], ['18:00:00:00', '18:00:01:16', '18:00:03:17']), ('normal control', ['18:00:00:00', [], 1, 25], ['18:00:00:00']), ('normal control', ['00:00:00:00', [], 0, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 25], ['00:00:00:00'])], [('regression: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '01:00:30:00'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '15:00:20:26', '16:00:50:27']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['10:00:00:00', '00:00:01:00'], ['10:00:00:00', '00:00:00:10']], 1, 30], ['00:00:00:00', '14:00:01:02', '04:00:01:13']), ('normal control', ['00:00:00:00', [], 0, 30], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 1, 30], ['23:59:50:00'])], [('regression: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('regression variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('partial repair probe: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 5, 25], ['23:59:50:00', '13:59:50:01']), ('normal control', ['23:59:50:00', [], 0, 25], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['18:00:00:00', [], 25, 30], ['18:00:00:00'])]]
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: span operand order['18:00:00:00', '10:00:01:00']['18:00:00:00', '18:00:01:00']Failed
regression variant: span operand order['23:59:50:00', '00:00:00:01']['23:59:50:00', '13:59:50:01']Failed
partial repair probe: span operand order['23:59:50:00', '00:00:01:06', '10:00:41:26', '11:01:21:27']['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']Failed
partial repair variant: span operand order['18:00:00:00', '00:00:00:11', '16:00:10:12', '22:00:10:13', '14:00:40:13']['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']Failed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['23:59:50:00']['23:59:50:00']Passed

SHA-256 / 68c8d3ae8987d6e3defbe8986f52febeddd9fbe456bd91de393b29b093ce8ded

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(start, clips, gap, fps):
    def fr(t):
        h,m,s,f=map(int,t.split(':'))
        return ((h*60+m)*60+s)*fps+f
    def lab(n):
        n%=86400*fps
        return '%02d:%02d:%02d:%02d'%(n//(3600*fps),n//(60*fps)%60,n//fps%60,n%fps)
    t=fr(start)
    out=[]
    for i,(som,eom) in enumerate(clips):
        if i:
            t+=gap
        out.append(lab(t))
        d=(fr(eom)-fr(som))%(86400*fps)
        t+=d+1
    out.append(lab(t))
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: span operand order', ['18:00:00:00', [['10:00:00:00', '10:00:00:24']], 0, 25], ['18:00:00:00', '18:00:01:00']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 30], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 25, 30], ['23:59:50:00'])], [('regression: span operand order', ['23:59:59:00', [['00:00:00:00', '00:00:01:00'], ['00:00:00:00', '00:00:00:00']], 5, 25], ['23:59:59:00', '00:00:00:06', '00:00:00:07']), ('regression variant: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair probe: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['00:00:00:00', '00:00:00:10'], ['10:00:00:00', '01:00:30:00'], ['10:00:00:00', '00:00:01:00'], ['00:00:00:00', '10:00:29:24']], 0, 25], ['00:00:00:00', '00:00:00:11', '15:00:30:12', '05:00:31:13', '15:01:01:13']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 1, 25], ['23:59:50:00']), ('normal control', ['00:00:00:00', [], 25, 30], ['00:00:00:00'])], [('regression: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:10'], ['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']), ('regression variant: span operand order', ['18:00:00:00', [['00:00:00:00', '10:00:29:24'], ['00:00:00:00', '10:00:10:00']], 0, 30], ['18:00:00:00', '04:00:29:25', '14:00:39:26']), ('partial repair probe: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('partial repair variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['23:59:59:00', '00:00:01:00']], 5, 25], ['18:00:00:00', '18:00:01:16', '18:00:03:17']), ('normal control', ['18:00:00:00', [], 1, 25], ['18:00:00:00']), ('normal control', ['00:00:00:00', [], 0, 25], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 5, 25], ['00:00:00:00'])], [('regression: span operand order', ['18:00:00:00', [['23:59:59:00', '01:00:30:00']], 5, 30], ['18:00:00:00', '19:00:31:01']), ('regression variant: span operand order', ['23:59:50:00', [['10:00:00:00', '01:00:30:00'], ['00:00:00:00', '01:00:30:00']], 25, 30], ['23:59:50:00', '15:00:20:26', '16:00:50:27']), ('partial repair probe: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 25, 30], ['23:59:50:00', '13:59:50:01']), ('partial repair variant: span operand order', ['00:00:00:00', [['10:00:00:00', '00:00:01:00'], ['10:00:00:00', '00:00:00:10']], 1, 30], ['00:00:00:00', '14:00:01:02', '04:00:01:13']), ('normal control', ['00:00:00:00', [], 0, 30], ['00:00:00:00']), ('normal control', ['00:00:00:00', [], 25, 25], ['00:00:00:00']), ('normal control', ['23:59:50:00', [], 1, 30], ['23:59:50:00'])], [('regression: span operand order', ['18:00:00:00', [['00:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:29:24'], ['23:59:59:00', '00:00:01:00']], 0, 25], ['18:00:00:00', '18:00:01:01', '03:00:31:01', '03:00:33:02']), ('regression variant: span operand order', ['18:00:00:00', [['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '10:00:10:00'], ['00:00:00:00', '00:00:00:00'], ['01:00:00:00', '10:00:29:24']], 0, 25], ['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']), ('partial repair probe: span operand order', ['18:00:00:00', [['01:00:00:00', '00:00:01:00'], ['01:00:00:00', '10:00:10:00'], ['23:59:59:00', '00:00:00:10'], ['00:00:00:00', '00:00:00:10']], 25, 25], ['18:00:00:00', '17:00:02:01', '02:00:13:02', '02:00:15:13', '02:00:15:24']), ('partial repair variant: span operand order', ['23:59:50:00', [['10:00:00:00', '00:00:00:00']], 5, 25], ['23:59:50:00', '13:59:50:01']), ('normal control', ['23:59:50:00', [], 0, 25], ['23:59:50:00']), ('normal control', ['23:59:50:00', [], 0, 30], ['23:59:50:00']), ('normal control', ['18:00:00:00', [], 25, 30], ['18:00:00:00'])]]
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: span operand order['18:00:00:00', '18:00:01:00']['18:00:00:00', '18:00:01:00']Passed
regression variant: span operand order['23:59:50:00', '13:59:50:01']['23:59:50:00', '13:59:50:01']Passed
partial repair probe: span operand order['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']['23:59:50:00', '13:59:51:06', '00:00:21:26', '01:00:51:27']Passed
partial repair variant: span operand order['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']['18:00:00:00', '18:00:01:11', '04:00:11:12', '04:00:11:13', '13:00:41:13']Passed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['00:00:00:00']['00:00:00:00']Passed
normal control['23:59:50:00']['23:59:50:00']Passed

SHA-256 / e710f472619a080bb8124764242ccd8fcc18ba96ec8db657158e2822977c6efb

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 2026-09-29T14:49:37.976289+00:00.

Case digest / a086722821b04808899356d3989bf662383ceef5927253775ac7546374324e32