FA-46651 / Bounded deques / Open access
Deque iterator batch counts entries before its cursor as remaining · case 01
Deque iterator batch counts entries before its cursor as remaining.
ROOT CAUSE
Deque iterator batch counts entries before its cursor as remaining.
VERIFIED REPAIR
Restore the documented remaining origin 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=len(a)
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', 3, [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 / f55d6a05a8a83777555fcd2e40df4fff1eea99ff4d9de58ab223014d90c9eb69
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) if pos==0 else len(a)
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', 3, [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 / 2e5e3ec7dc3af52558a0b532fa2b066f96a79081775b1d0f2dd0fd1e12efba22
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 2026-09-29T14:44:34.115138+00:00.
Case digest / ad84ed320be70f0f45f3960a2eea1c3c4de9c790b19e52d01f18194cdcbf6134