FAILURE MAP
← Case archive

FA-35871 / Tab interfaces / Open access

Linked pane scroll: peer end clamp · case 01

The tab workspace reports an incorrect peer end clamp.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The peer end clamp decision uses min(x['source_range'],x['scroll']*x['peer_range']//x['source_range']) instead of min(x['peer_range'],max(0,x['scroll']*x['peer_range']//x['source_range'])).

VERIFIED REPAIR

Use the stipulated workspace rule: min(x['peer_range'],max(0,x['scroll']*x['peer_range']//x['source_range'])).

Unsuccessful approach: The partial repair max(0,x['scroll']) still violates a workspace boundary or normal case.

Case contract

Linked views of one document synchronize only scroll events from the elected source; map proportional content positions into the peer range and suppress echoed tokens.

Why this case matters

Offline tab/panel workspace behavior; no browser or desktop framework is emulated.

1 / The failure

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

N = 1
observations = []
def solve(x):
    r0 = x['event_view']==x['source']
    r1 = x['doc']==x['peer_doc']
    r2 = x['token']!=x['last']
    r3 = x['scroll']*x['peer_range']//x['source_range']
    r4 = min(x['source_range'],x['scroll']*x['peer_range']//x['source_range'])
    r5 = x['token']
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [False, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, False, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 3, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, False, 100, 100, 3]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 0, 'source_range': 100, 'peer_range': 250}, [True, True, True, 0, 0, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 100, 'source_range': 100, 'peer_range': 250}, [True, True, True, 250, 250, 4])], 2: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [False, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, False, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 6, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, False, 200, 200, 6]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 0, 'source_range': 200, 'peer_range': 500}, [True, True, True, 0, 0, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 200, 'source_range': 200, 'peer_range': 500}, [True, True, True, 500, 500, 8])], 3: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [False, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, False, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 9, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, False, 300, 300, 9]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 0, 'source_range': 300, 'peer_range': 750}, [True, True, True, 0, 0, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 300, 'source_range': 300, 'peer_range': 750}, [True, True, True, 750, 750, 12])], 4: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [False, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, False, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, False, 400, 400, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 0, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 0, 0, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 400, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 1000, 1000, 16])], 5: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [False, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, False, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 15, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, False, 500, 500, 15]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 0, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 0, 0, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 500, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 1250, 1250, 20])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[True, True, True, 100, 100, 4][True, True, True, 100, 100, 4]Passed
workspace regression 1[False, True, True, 100, 100, 4][False, True, True, 100, 100, 4]Passed
workspace regression 2[True, False, True, 100, 100, 4][True, False, True, 100, 100, 4]Passed
workspace regression 3[True, True, False, 100, 100, 3][True, True, False, 100, 100, 3]Passed
workspace regression 4[True, True, True, 0, 0, 4][True, True, True, 0, 0, 4]Passed
workspace regression 5[True, True, True, 250, 100, 4][True, True, True, 250, 250, 4]Failed

SHA-256 / 65fd73d78ae1e8e034d05ccf8936f965055ed552415b0d21e367f1df08b37ac7

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(x):
    r0 = x['event_view']==x['source']
    r1 = x['doc']==x['peer_doc']
    r2 = x['token']!=x['last']
    r3 = x['scroll']*x['peer_range']//x['source_range']
    r4 = max(0,x['scroll'])
    r5 = x['token']
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [False, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, False, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 3, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, False, 100, 100, 3]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 0, 'source_range': 100, 'peer_range': 250}, [True, True, True, 0, 0, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 100, 'source_range': 100, 'peer_range': 250}, [True, True, True, 250, 250, 4])], 2: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [False, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, False, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 6, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, False, 200, 200, 6]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 0, 'source_range': 200, 'peer_range': 500}, [True, True, True, 0, 0, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 200, 'source_range': 200, 'peer_range': 500}, [True, True, True, 500, 500, 8])], 3: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [False, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, False, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 9, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, False, 300, 300, 9]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 0, 'source_range': 300, 'peer_range': 750}, [True, True, True, 0, 0, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 300, 'source_range': 300, 'peer_range': 750}, [True, True, True, 750, 750, 12])], 4: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [False, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, False, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, False, 400, 400, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 0, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 0, 0, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 400, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 1000, 1000, 16])], 5: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [False, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, False, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 15, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, False, 500, 500, 15]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 0, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 0, 0, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 500, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 1250, 1250, 20])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[True, True, True, 100, 40, 4][True, True, True, 100, 100, 4]Failed
workspace regression 1[False, True, True, 100, 40, 4][False, True, True, 100, 100, 4]Failed
workspace regression 2[True, False, True, 100, 40, 4][True, False, True, 100, 100, 4]Failed
workspace regression 3[True, True, False, 100, 40, 3][True, True, False, 100, 100, 3]Failed
workspace regression 4[True, True, True, 0, 0, 4][True, True, True, 0, 0, 4]Passed
workspace regression 5[True, True, True, 250, 100, 4][True, True, True, 250, 250, 4]Failed

SHA-256 / 0e2f91f918ed5dfeea90ddbe5c952a59230b1e63065fc511e9ff20fbc1cac547

3 / The verified repair

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

N = 1
observations = []
def solve(x):
    r0 = x['event_view']==x['source']
    r1 = x['doc']==x['peer_doc']
    r2 = x['token']!=x['last']
    r3 = x['scroll']*x['peer_range']//x['source_range']
    r4 = min(x['peer_range'],max(0,x['scroll']*x['peer_range']//x['source_range']))
    r5 = x['token']
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [False, True, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 4, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, False, True, 100, 100, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 3, 'last': 3, 'scroll': 40, 'source_range': 100, 'peer_range': 250}, [True, True, False, 100, 100, 3]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 0, 'source_range': 100, 'peer_range': 250}, [True, True, True, 0, 0, 4]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 4, 'last': 3, 'scroll': 100, 'source_range': 100, 'peer_range': 250}, [True, True, True, 250, 250, 4])], 2: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [False, True, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 8, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, False, True, 200, 200, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 6, 'last': 6, 'scroll': 80, 'source_range': 200, 'peer_range': 500}, [True, True, False, 200, 200, 6]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 0, 'source_range': 200, 'peer_range': 500}, [True, True, True, 0, 0, 8]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 8, 'last': 6, 'scroll': 200, 'source_range': 200, 'peer_range': 500}, [True, True, True, 500, 500, 8])], 3: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [False, True, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 12, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, False, True, 300, 300, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 9, 'last': 9, 'scroll': 120, 'source_range': 300, 'peer_range': 750}, [True, True, False, 300, 300, 9]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 0, 'source_range': 300, 'peer_range': 750}, [True, True, True, 0, 0, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 9, 'scroll': 300, 'source_range': 300, 'peer_range': 750}, [True, True, True, 750, 750, 12])], 4: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [False, True, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 16, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, False, True, 400, 400, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 12, 'last': 12, 'scroll': 160, 'source_range': 400, 'peer_range': 1000}, [True, True, False, 400, 400, 12]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 0, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 0, 0, 16]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 16, 'last': 12, 'scroll': 400, 'source_range': 400, 'peer_range': 1000}, [True, True, True, 1000, 1000, 16])], 5: [({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'b', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [False, True, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'e', 'token': 20, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, False, True, 500, 500, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 15, 'last': 15, 'scroll': 200, 'source_range': 500, 'peer_range': 1250}, [True, True, False, 500, 500, 15]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 0, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 0, 0, 20]), ({'source': 'a', 'event_view': 'a', 'doc': 'd', 'peer_doc': 'd', 'token': 20, 'last': 15, 'scroll': 500, 'source_range': 500, 'peer_range': 1250}, [True, True, True, 1250, 1250, 20])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[True, True, True, 100, 100, 4][True, True, True, 100, 100, 4]Passed
workspace regression 1[False, True, True, 100, 100, 4][False, True, True, 100, 100, 4]Passed
workspace regression 2[True, False, True, 100, 100, 4][True, False, True, 100, 100, 4]Passed
workspace regression 3[True, True, False, 100, 100, 3][True, True, False, 100, 100, 3]Passed
workspace regression 4[True, True, True, 0, 0, 4][True, True, True, 0, 0, 4]Passed
workspace regression 5[True, True, True, 250, 250, 4][True, True, True, 250, 250, 4]Passed

SHA-256 / 8b7c65341074705a361da484f48e02a22dbd87888632c6f8e0061a3a6d96df15

Verification & scope

Finite stipulated workspace snapshots only. Independent result fields describe observable obligations, not a full UI runtime. 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 2026-09-29T14:42:45.675210+00:00.

Case digest / 03a3389c23434d9d5baf6f57d2a0dd7918701d00491c22862a27bc6846db35e4