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FA-46666 / Bounded deques / Open access

Deque iterator rereads the beginning on subsequent batches · case 01

Deque iterator rereads the beginning on subsequent batches.

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

ROOT CAUSE

Deque iterator rereads the beginning on subsequent batches.

THE FAILURE

Deque iterator rereads the beginning on subsequent batches.

Unsuccessful approach: The partial repair still applies the incorrect transition to an admitted boundary or multi-element case.

Case contract

A fail-fast deque iterator tracks consumed logical count, captured structural epoch and traversal direction. Read at most limit elements; stale iterators emit no items and preserve position.

Why this case matters

Controlled bounded deque implementation model with explicit storage and lifecycle observations.

1 / The failure

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

N = 1
observations = []
def solve(x):
    a,pos,limit,saved,current,reverse=x
    if saved!=current:return ['stale',pos,[],saved]
    remaining=max(0,len(a)-pos)
    count=min(limit,remaining)
    sequence=a[::-1] if reverse else a
    values=sequence[:count]
    next_pos=pos+count
    return ['ok',next_pos,values,saved]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([[N,N+1,N+2,N+3],1,2,3,3,False]), {1: ['ok', 3, [2, 3], 3], 2: ['ok', 3, [3, 4], 3], 3: ['ok', 3, [4, 5], 3], 4: ['ok', 3, [5, 6], 3], 5: ['ok', 3, [6, 7], 3]}[N])
check('1', solve([[N,N+1,N+2],0,2,2,2,True]), {1: ['ok', 2, [3, 2], 2], 2: ['ok', 2, [4, 3], 2], 3: ['ok', 2, [5, 4], 2], 4: ['ok', 2, [6, 5], 2], 5: ['ok', 2, [7, 6], 2]}[N])
check('2', solve([[N,N+1],1,5,4,4,False]), {1: ['ok', 2, [2], 4], 2: ['ok', 2, [3], 4], 3: ['ok', 2, [4], 4], 4: ['ok', 2, [5], 4], 5: ['ok', 2, [6], 4]}[N])
check('3', solve([[N],0,3,1,2,False]), {1: ['stale', 0, [], 1], 2: ['stale', 0, [], 1], 3: ['stale', 0, [], 1], 4: ['stale', 0, [], 1], 5: ['stale', 0, [], 1]}[N])
check('4', solve([[],0,2,0,0,True]), {1: ['ok', 0, [], 0], 2: ['ok', 0, [], 0], 3: ['ok', 0, [], 0], 4: ['ok', 0, [], 0], 5: ['ok', 0, [], 0]}[N])
check('5', solve([[N,N+1],1,0,5,5,True]), {1: ['ok', 1, [], 5], 2: ['ok', 1, [], 5], 3: ['ok', 1, [], 5], 4: ['ok', 1, [], 5], 5: ['ok', 1, [], 5]}[N])
check('6', solve([[N,N+1],0,1,3,2,False]), {1: ['stale', 0, [], 3], 2: ['stale', 0, [], 3], 3: ['stale', 0, [], 3], 4: ['stale', 0, [], 3], 5: ['stale', 0, [], 3]}[N])
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
0['ok', 3, [1, 2], 3]['ok', 3, [2, 3], 3]Failed
1['ok', 2, [3, 2], 2]['ok', 2, [3, 2], 2]Passed
2['ok', 2, [1], 4]['ok', 2, [2], 4]Failed
3['stale', 0, [], 1]['stale', 0, [], 1]Passed
4['ok', 0, [], 0]['ok', 0, [], 0]Passed
5['ok', 1, [], 5]['ok', 1, [], 5]Passed
6['stale', 0, [], 3]['stale', 0, [], 3]Passed

SHA-256 / 35990f66c34dc4d61e2fd21d6f853d2efc74e68122777f1728f26bdb9f31d224

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(x):
    a,pos,limit,saved,current,reverse=x
    if saved!=current:return ['stale',pos,[],saved]
    remaining=max(0,len(a)-pos)
    count=min(limit,remaining)
    sequence=a[::-1] if reverse else a
    values=sequence[pos:pos+count] if pos<=0 else sequence[:count]
    next_pos=pos+count
    return ['ok',next_pos,values,saved]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([[N,N+1,N+2,N+3],1,2,3,3,False]), {1: ['ok', 3, [2, 3], 3], 2: ['ok', 3, [3, 4], 3], 3: ['ok', 3, [4, 5], 3], 4: ['ok', 3, [5, 6], 3], 5: ['ok', 3, [6, 7], 3]}[N])
check('1', solve([[N,N+1,N+2],0,2,2,2,True]), {1: ['ok', 2, [3, 2], 2], 2: ['ok', 2, [4, 3], 2], 3: ['ok', 2, [5, 4], 2], 4: ['ok', 2, [6, 5], 2], 5: ['ok', 2, [7, 6], 2]}[N])
check('2', solve([[N,N+1],1,5,4,4,False]), {1: ['ok', 2, [2], 4], 2: ['ok', 2, [3], 4], 3: ['ok', 2, [4], 4], 4: ['ok', 2, [5], 4], 5: ['ok', 2, [6], 4]}[N])
check('3', solve([[N],0,3,1,2,False]), {1: ['stale', 0, [], 1], 2: ['stale', 0, [], 1], 3: ['stale', 0, [], 1], 4: ['stale', 0, [], 1], 5: ['stale', 0, [], 1]}[N])
check('4', solve([[],0,2,0,0,True]), {1: ['ok', 0, [], 0], 2: ['ok', 0, [], 0], 3: ['ok', 0, [], 0], 4: ['ok', 0, [], 0], 5: ['ok', 0, [], 0]}[N])
check('5', solve([[N,N+1],1,0,5,5,True]), {1: ['ok', 1, [], 5], 2: ['ok', 1, [], 5], 3: ['ok', 1, [], 5], 4: ['ok', 1, [], 5], 5: ['ok', 1, [], 5]}[N])
check('6', solve([[N,N+1],0,1,3,2,False]), {1: ['stale', 0, [], 3], 2: ['stale', 0, [], 3], 3: ['stale', 0, [], 3], 4: ['stale', 0, [], 3], 5: ['stale', 0, [], 3]}[N])
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
0['ok', 3, [1, 2], 3]['ok', 3, [2, 3], 3]Failed
1['ok', 2, [3, 2], 2]['ok', 2, [3, 2], 2]Passed
2['ok', 2, [1], 4]['ok', 2, [2], 4]Failed
3['stale', 0, [], 1]['stale', 0, [], 1]Passed
4['ok', 0, [], 0]['ok', 0, [], 0]Passed
5['ok', 1, [], 5]['ok', 1, [], 5]Passed
6['stale', 0, [], 3]['stale', 0, [], 3]Passed

SHA-256 / 1b00a5843fd7c62a8f8c9da0df4d61c26f6f867c799c2583028176ae18926a67

HELD IN THE MEMBER ARCHIVE

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

This mechanism has 7 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

Offline finite deterministic model; no claim of production implementation or concurrent memory-model conformance. 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 2026-09-29T14:44:34.315747+00:00.

Case digest / 8bd2c7dd39c7bff1e0d2c8a552aac90c973883a8ec40795c99aed58ce8cdf8d0