FA-46671 / Bounded deques / Open access
Deque iterator advances by request rather than actual delivery · case 01
Deque iterator advances by request rather than actual delivery.
ROOT CAUSE
Deque iterator advances by request rather than actual delivery.
VERIFIED REPAIR
Restore the documented cursor advance invariant in iterator-batch.
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[pos:pos+count]
next_pos=pos+limit
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| 0 | ['ok', 3, [2, 3], 3] | ['ok', 3, [2, 3], 3] | Passed |
| 1 | ['ok', 2, [3, 2], 2] | ['ok', 2, [3, 2], 2] | Passed |
| 2 | ['ok', 6, [2], 4] | ['ok', 2, [2], 4] | Failed |
| 3 | ['stale', 0, [], 1] | ['stale', 0, [], 1] | Passed |
| 4 | ['ok', 2, [], 0] | ['ok', 0, [], 0] | Failed |
| 5 | ['ok', 1, [], 5] | ['ok', 1, [], 5] | Passed |
| 6 | ['stale', 0, [], 3] | ['stale', 0, [], 3] | Passed |
SHA-256 / ebfabaf6b21c6622ada2365744e5037c9f6c18c0be50963d4e8e87c1532b2c8f
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]
next_pos=pos+count if count==0 else pos+limit
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| 0 | ['ok', 3, [2, 3], 3] | ['ok', 3, [2, 3], 3] | Passed |
| 1 | ['ok', 2, [3, 2], 2] | ['ok', 2, [3, 2], 2] | Passed |
| 2 | ['ok', 6, [2], 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 / 3d5648902392ad17af85c132807cdf3976196dc162a2e0d977c521bb45b3aad5
3 / The verified repair
Exit 0"""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]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| 0 | ['ok', 3, [2, 3], 3] | ['ok', 3, [2, 3], 3] | Passed |
| 1 | ['ok', 2, [3, 2], 2] | ['ok', 2, [3, 2], 2] | Passed |
| 2 | ['ok', 2, [2], 4] | ['ok', 2, [2], 4] | Passed |
| 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 / 8df25ac41577cafa3cbc155288b37068a18d0629d53c7c9caf1961c097a09b0c
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 / cd6d402b2b1824748927eed8c59a10b403ec05710fd3faf6b8ad94c7dd75a68d