FA-77981 / Subtitle cue timing / Open access

Minimum gap and chaining between cues: chain target · case 01

Chained cues touch the next cue with no separating gap.

Verified by executionVariant 1 · 9 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Chaining extends the end all the way to the next start.

VERIFIED REPAIR

Extend the end to next_start - min_gap.

Unsuccessful approach: Subtracting the chain threshold moves the end backwards instead of closing the gap.

Case contract

For sorted cues [start,end], compare each cue with the next start. If gap = next_start - end is below min_gap, the end is trimmed to next_start - min_gap but never below start+1. If min_gap <= gap < chain, the end is extended to next_start - min_gap. Larger gaps are untouched.

Why this case matters

Subtitle timing defects shift, hide or overlap captions that viewers depend on for comprehension and accessibility.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(cues, min_gap, chain):
    out=[list(c) for c in cues]
    for i in range(len(out)-1):
        cur=out[i]
        nxt_start=out[i+1][0]
        gap=nxt_start-cur[1]
        if gap<min_gap:
            cur[1]=max(cur[0]+1,nxt_start-min_gap)
        elif gap<chain:
            cur[1]=nxt_start
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: chain target', [[[0, 1000], [1400, 2000]], 100, 500], [[0, 1300], [1400, 2000]]), ('regression variant: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair probe: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('partial repair variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[0, 400], [1400, 2400]], 80, 750], [[0, 400], [1400, 2400]]), ('normal control', [[[0, 1000], [1301, 1401]], 100, 300], [[0, 1000], [1301, 1401]])], [('regression: chain target', [[[0, 100], [183, 2183], [3183, 3283], [3784, 5784]], 83, 500], [[0, 100], [183, 2183], [3183, 3283], [3784, 5784]]), ('regression variant: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair probe: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('partial repair variant: chain target', [[[0, 1000], [2000, 2400], [2899, 2999]], 120, 500], [[0, 1000], [2000, 2779], [2899, 2999]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 2000], [2030, 2430]], 83, 300], [[1000, 1947], [2030, 2430]]), ('normal control', [[[0, 400], [1270, 1370], [2240, 2340]], 120, 750], [[0, 400], [1270, 1370], [2240, 2340]]), ('normal control', [[[1000, 3000], [4000, 6000], [6030, 6430], [6230, 8230], [8030, 10030]], 80, 750], [[1000, 3000], [4000, 5950], [6030, 6150], [6230, 7950], [8030, 10030]])], [('regression: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('regression variant: chain target', [[[0, 400], [983, 1083], [1165, 1265], [1166, 2166], [2250, 2350]], 83, 500], [[0, 400], [983, 1082], [1165, 1166], [1166, 2167], [2250, 2350]]), ('partial repair probe: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('partial repair variant: chain target', [[[0, 2000], [2083, 4083], [4113, 4513], [4896, 4996], [5295, 6295]], 83, 300], [[0, 2000], [2083, 4030], [4113, 4513], [4896, 5212], [5295, 6295]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('normal control', [[[1000, 3000], [3383, 4383], [4333, 6333]], 83, 300], [[1000, 3000], [3383, 4250], [4333, 6333]]), ('normal control', [[[0, 100], [182, 582]], 83, 300], [[0, 99], [182, 582]]), ('normal control', [[[0, 2000], [2000, 4000], [3950, 4950]], 100, 750], [[0, 1900], [2000, 3850], [3950, 4950]])], [('regression: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('regression variant: chain target', [[[0, 2000], [2499, 3499], [3598, 3698]], 100, 500], [[0, 2399], [2499, 3498], [3598, 3698]]), ('partial repair probe: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair variant: chain target', [[[1000, 1400], [1899, 2299], [2099, 2499]], 80, 500], [[1000, 1819], [1899, 2019], [2099, 2499]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [1833, 2833]], 83, 750], [[0, 1000], [1833, 2833]]), ('normal control', [[[1000, 3000], [3000, 3100], [4100, 6100], [6050, 8050], [8801, 10801]], 80, 750], [[1000, 2920], [3000, 3100], [4100, 5970], [6050, 8050], [8801, 10801]]), ('normal control', [[[0, 2000], [2000, 2100], [2130, 2530], [2560, 2660], [2610, 3010]], 120, 750], [[0, 1880], [2000, 2010], [2130, 2440], [2560, 2561], [2610, 3010]])], [('regression: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('regression variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('partial repair probe: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair variant: chain target', [[[1000, 3000], [3005, 4005], [4105, 5105], [5606, 6006]], 100, 500], [[1000, 2905], [3005, 4005], [4105, 5105], [5606, 6006]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 1400], [1482, 1582]], 83, 300], [[1000, 1399], [1482, 1582]]), ('normal control', [[[1000, 1400], [1400, 3400], [3350, 3750]], 100, 500], [[1000, 1300], [1400, 3250], [3350, 3750]]), ('normal control', [[[0, 2000], [1950, 3950], [3900, 4300]], 100, 500], [[0, 1850], [1950, 3800], [3900, 4300]])]]
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 fixture	Actual	Expected	Outcome
regression: chain target	`[[0, 1400], [1400, 2000]]`	`[[0, 1300], [1400, 2000]]`	Failed
regression variant: chain target	`[[1000, 2947], [3030, 5113], [5113, 6113], [6864, 6881], [6964, 8964]]`	`[[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]`	Failed
partial repair probe: chain target	`[[0, 930], [1030, 2131], [2131, 4131], [4882, 5882]]`	`[[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]`	Failed
partial repair variant: chain target	`[[0, 2000], [2830, 3911], [3911, 4911], [5741, 6141], [6891, 8891]]`	`[[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]`	Failed
boundary control	`[[0, 950], [1050, 2000]]`	`[[0, 950], [1050, 2000]]`	Passed
boundary control	`[[0, 1000], [1500, 2000]]`	`[[0, 1000], [1500, 2000]]`	Passed
normal control	`[[0, 800], [900, 2000]]`	`[[0, 800], [900, 2000]]`	Passed
normal control	`[[0, 400], [1400, 2400]]`	`[[0, 400], [1400, 2400]]`	Passed
normal control	`[[0, 1000], [1301, 1401]]`	`[[0, 1000], [1301, 1401]]`	Passed

SHA-256 / e08291fd01acea7acd286e3674c1ac263b2d695a99a539bfba6144dc192bfd66

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(cues, min_gap, chain):
    out=[list(c) for c in cues]
    for i in range(len(out)-1):
        cur=out[i]
        nxt_start=out[i+1][0]
        gap=nxt_start-cur[1]
        if gap<min_gap:
            cur[1]=max(cur[0]+1,nxt_start-min_gap)
        elif gap<chain:
            cur[1]=nxt_start-chain
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: chain target', [[[0, 1000], [1400, 2000]], 100, 500], [[0, 1300], [1400, 2000]]), ('regression variant: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair probe: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('partial repair variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[0, 400], [1400, 2400]], 80, 750], [[0, 400], [1400, 2400]]), ('normal control', [[[0, 1000], [1301, 1401]], 100, 300], [[0, 1000], [1301, 1401]])], [('regression: chain target', [[[0, 100], [183, 2183], [3183, 3283], [3784, 5784]], 83, 500], [[0, 100], [183, 2183], [3183, 3283], [3784, 5784]]), ('regression variant: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair probe: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('partial repair variant: chain target', [[[0, 1000], [2000, 2400], [2899, 2999]], 120, 500], [[0, 1000], [2000, 2779], [2899, 2999]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 2000], [2030, 2430]], 83, 300], [[1000, 1947], [2030, 2430]]), ('normal control', [[[0, 400], [1270, 1370], [2240, 2340]], 120, 750], [[0, 400], [1270, 1370], [2240, 2340]]), ('normal control', [[[1000, 3000], [4000, 6000], [6030, 6430], [6230, 8230], [8030, 10030]], 80, 750], [[1000, 3000], [4000, 5950], [6030, 6150], [6230, 7950], [8030, 10030]])], [('regression: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('regression variant: chain target', [[[0, 400], [983, 1083], [1165, 1265], [1166, 2166], [2250, 2350]], 83, 500], [[0, 400], [983, 1082], [1165, 1166], [1166, 2167], [2250, 2350]]), ('partial repair probe: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('partial repair variant: chain target', [[[0, 2000], [2083, 4083], [4113, 4513], [4896, 4996], [5295, 6295]], 83, 300], [[0, 2000], [2083, 4030], [4113, 4513], [4896, 5212], [5295, 6295]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('normal control', [[[1000, 3000], [3383, 4383], [4333, 6333]], 83, 300], [[1000, 3000], [3383, 4250], [4333, 6333]]), ('normal control', [[[0, 100], [182, 582]], 83, 300], [[0, 99], [182, 582]]), ('normal control', [[[0, 2000], [2000, 4000], [3950, 4950]], 100, 750], [[0, 1900], [2000, 3850], [3950, 4950]])], [('regression: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('regression variant: chain target', [[[0, 2000], [2499, 3499], [3598, 3698]], 100, 500], [[0, 2399], [2499, 3498], [3598, 3698]]), ('partial repair probe: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair variant: chain target', [[[1000, 1400], [1899, 2299], [2099, 2499]], 80, 500], [[1000, 1819], [1899, 2019], [2099, 2499]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [1833, 2833]], 83, 750], [[0, 1000], [1833, 2833]]), ('normal control', [[[1000, 3000], [3000, 3100], [4100, 6100], [6050, 8050], [8801, 10801]], 80, 750], [[1000, 2920], [3000, 3100], [4100, 5970], [6050, 8050], [8801, 10801]]), ('normal control', [[[0, 2000], [2000, 2100], [2130, 2530], [2560, 2660], [2610, 3010]], 120, 750], [[0, 1880], [2000, 2010], [2130, 2440], [2560, 2561], [2610, 3010]])], [('regression: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('regression variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('partial repair probe: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair variant: chain target', [[[1000, 3000], [3005, 4005], [4105, 5105], [5606, 6006]], 100, 500], [[1000, 2905], [3005, 4005], [4105, 5105], [5606, 6006]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 1400], [1482, 1582]], 83, 300], [[1000, 1399], [1482, 1582]]), ('normal control', [[[1000, 1400], [1400, 3400], [3350, 3750]], 100, 500], [[1000, 1300], [1400, 3250], [3350, 3750]]), ('normal control', [[[0, 2000], [1950, 3950], [3900, 4300]], 100, 500], [[0, 1850], [1950, 3800], [3900, 4300]])]]
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 fixture	Actual	Expected	Outcome
regression: chain target	`[[0, 900], [1400, 2000]]`	`[[0, 1300], [1400, 2000]]`	Failed
regression variant: chain target	`[[1000, 2947], [3030, 4363], [5113, 6113], [6864, 6881], [6964, 8964]]`	`[[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]`	Failed
partial repair probe: chain target	`[[0, 930], [1030, 1381], [2131, 4131], [4882, 5882]]`	`[[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]`	Failed
partial repair variant: chain target	`[[0, 2000], [2830, 3161], [3911, 4911], [5741, 6141], [6891, 8891]]`	`[[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]`	Failed
boundary control	`[[0, 950], [1050, 2000]]`	`[[0, 950], [1050, 2000]]`	Passed
boundary control	`[[0, 1000], [1500, 2000]]`	`[[0, 1000], [1500, 2000]]`	Passed
normal control	`[[0, 800], [900, 2000]]`	`[[0, 800], [900, 2000]]`	Passed
normal control	`[[0, 400], [1400, 2400]]`	`[[0, 400], [1400, 2400]]`	Passed
normal control	`[[0, 1000], [1301, 1401]]`	`[[0, 1000], [1301, 1401]]`	Passed

SHA-256 / 9f4811f6fb70d3d370a5b4a6de44f5cb27277581879ad21551b4cd2f2a92147c

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(cues, min_gap, chain):
    out=[list(c) for c in cues]
    for i in range(len(out)-1):
        cur=out[i]
        nxt_start=out[i+1][0]
        gap=nxt_start-cur[1]
        if gap<min_gap:
            cur[1]=max(cur[0]+1,nxt_start-min_gap)
        elif gap<chain:
            cur[1]=nxt_start-min_gap
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: chain target', [[[0, 1000], [1400, 2000]], 100, 500], [[0, 1300], [1400, 2000]]), ('regression variant: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair probe: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('partial repair variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[0, 400], [1400, 2400]], 80, 750], [[0, 400], [1400, 2400]]), ('normal control', [[[0, 1000], [1301, 1401]], 100, 300], [[0, 1000], [1301, 1401]])], [('regression: chain target', [[[0, 100], [183, 2183], [3183, 3283], [3784, 5784]], 83, 500], [[0, 100], [183, 2183], [3183, 3283], [3784, 5784]]), ('regression variant: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair probe: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('partial repair variant: chain target', [[[0, 1000], [2000, 2400], [2899, 2999]], 120, 500], [[0, 1000], [2000, 2779], [2899, 2999]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 2000], [2030, 2430]], 83, 300], [[1000, 1947], [2030, 2430]]), ('normal control', [[[0, 400], [1270, 1370], [2240, 2340]], 120, 750], [[0, 400], [1270, 1370], [2240, 2340]]), ('normal control', [[[1000, 3000], [4000, 6000], [6030, 6430], [6230, 8230], [8030, 10030]], 80, 750], [[1000, 3000], [4000, 5950], [6030, 6150], [6230, 7950], [8030, 10030]])], [('regression: chain target', [[[0, 1000], [1030, 2030], [2131, 4131], [4882, 5882]], 100, 750], [[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]), ('regression variant: chain target', [[[0, 400], [983, 1083], [1165, 1265], [1166, 2166], [2250, 2350]], 83, 500], [[0, 400], [983, 1082], [1165, 1166], [1166, 2167], [2250, 2350]]), ('partial repair probe: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('partial repair variant: chain target', [[[0, 2000], [2083, 4083], [4113, 4513], [4896, 4996], [5295, 6295]], 83, 300], [[0, 2000], [2083, 4030], [4113, 4513], [4896, 5212], [5295, 6295]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('normal control', [[[1000, 3000], [3383, 4383], [4333, 6333]], 83, 300], [[1000, 3000], [3383, 4250], [4333, 6333]]), ('normal control', [[[0, 100], [182, 582]], 83, 300], [[0, 99], [182, 582]]), ('normal control', [[[0, 2000], [2000, 4000], [3950, 4950]], 100, 750], [[0, 1900], [2000, 3850], [3950, 4950]])], [('regression: chain target', [[[1000, 2000], [2005, 2405], [2486, 2886], [3266, 5266], [5567, 6567]], 80, 300], [[1000, 1925], [2005, 2406], [2486, 2886], [3266, 5266], [5567, 6567]]), ('regression variant: chain target', [[[0, 2000], [2499, 3499], [3598, 3698]], 100, 500], [[0, 2399], [2499, 3498], [3598, 3698]]), ('partial repair probe: chain target', [[[1000, 3000], [3030, 5030], [5113, 6113], [6864, 6964], [6964, 8964]], 83, 750], [[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]), ('partial repair variant: chain target', [[[1000, 1400], [1899, 2299], [2099, 2499]], 80, 500], [[1000, 1819], [1899, 2019], [2099, 2499]]), ('boundary control', [[[0, 1000], [1050, 2000]], 100, 500], [[0, 950], [1050, 2000]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('normal control', [[[0, 1000], [1833, 2833]], 83, 750], [[0, 1000], [1833, 2833]]), ('normal control', [[[1000, 3000], [3000, 3100], [4100, 6100], [6050, 8050], [8801, 10801]], 80, 750], [[1000, 2920], [3000, 3100], [4100, 5970], [6050, 8050], [8801, 10801]]), ('normal control', [[[0, 2000], [2000, 2100], [2130, 2530], [2560, 2660], [2610, 3010]], 120, 750], [[0, 1880], [2000, 2010], [2130, 2440], [2560, 2561], [2610, 3010]])], [('regression: chain target', [[[1000, 1400], [1499, 1899], [2398, 2498], [2399, 2799], [2900, 3900]], 100, 500], [[1000, 1399], [1499, 2298], [2398, 2399], [2399, 2800], [2900, 3900]]), ('regression variant: chain target', [[[0, 2000], [2830, 3830], [3911, 4911], [5741, 6141], [6891, 8891]], 80, 750], [[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]), ('partial repair probe: chain target', [[[1000, 3000], [3005, 5005], [5084, 5484], [5565, 5965]], 80, 300], [[1000, 2925], [3005, 5004], [5084, 5485], [5565, 5965]]), ('partial repair variant: chain target', [[[1000, 3000], [3005, 4005], [4105, 5105], [5606, 6006]], 100, 500], [[1000, 2905], [3005, 4005], [4105, 5105], [5606, 6006]]), ('boundary control', [[[0, 1000], [1500, 2000]], 100, 500], [[0, 1000], [1500, 2000]]), ('boundary control', [[[0, 1000], [900, 2000]], 100, 500], [[0, 800], [900, 2000]]), ('normal control', [[[1000, 1400], [1482, 1582]], 83, 300], [[1000, 1399], [1482, 1582]]), ('normal control', [[[1000, 1400], [1400, 3400], [3350, 3750]], 100, 500], [[1000, 1300], [1400, 3250], [3350, 3750]]), ('normal control', [[[0, 2000], [1950, 3950], [3900, 4300]], 100, 500], [[0, 1850], [1950, 3800], [3900, 4300]])]]
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 fixture	Actual	Expected	Outcome
regression: chain target	`[[0, 1300], [1400, 2000]]`	`[[0, 1300], [1400, 2000]]`	Passed
regression variant: chain target	`[[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]`	`[[1000, 2947], [3030, 5030], [5113, 6113], [6864, 6881], [6964, 8964]]`	Passed
partial repair probe: chain target	`[[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]`	`[[0, 930], [1030, 2031], [2131, 4131], [4882, 5882]]`	Passed
partial repair variant: chain target	`[[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]`	`[[0, 2000], [2830, 3831], [3911, 4911], [5741, 6141], [6891, 8891]]`	Passed
boundary control	`[[0, 950], [1050, 2000]]`	`[[0, 950], [1050, 2000]]`	Passed
boundary control	`[[0, 1000], [1500, 2000]]`	`[[0, 1000], [1500, 2000]]`	Passed
normal control	`[[0, 800], [900, 2000]]`	`[[0, 800], [900, 2000]]`	Passed
normal control	`[[0, 400], [1400, 2400]]`	`[[0, 400], [1400, 2400]]`	Passed
normal control	`[[0, 1000], [1301, 1401]]`	`[[0, 1000], [1301, 1401]]`	Passed

SHA-256 / 18e27293dc18d3c91da2663b4b6ae3943fc7450b90fef108fd97cce06b57f0e1

Verification & scope

A deterministic bounded teaching model with a stipulated toy contract; it does not claim conformance to any subtitle 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 2026-09-29T14:49:30.775706+00:00.

Case digest / 18811f8c164e18d739b9137f780a72590ed694e62d58a2e3bbb6ed6a795f25f0