FA-47186 / Bounded deques / Open access
Deque pressure treats exact high occupancy as below high · case 01
Deque pressure treats exact high occupancy as below high.
ROOT CAUSE
Deque pressure treats exact high occupancy as below high.
VERIFIED REPAIR
Restore the documented high level invariant in watermark-transitions.
Unsuccessful approach: The partial repair still applies the incorrect transition to an admitted boundary or multi-element case.
Case contract
Bounded deque pressure notifications are edge-triggered: unpaused producers pause on an upward high crossing; paused producers resume on a downward low crossing. Return state, ordered notification list and distances to both thresholds.
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):
old,new,low,high,paused=x
events=[]
state=paused
if not paused and old<high<=new:
state=True
events.append('pause')
if paused and old>low>=new:
state=False
events.append('resume')
at_high=new>high
at_low=new<=low
headroom=max(0,high-new)
excess=max(0,new-low)
return [state,events,at_high,at_low,headroom,excess]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([2,5,2,5,False]), {1: [True, ['pause'], True, False, 0, 3], 2: [True, ['pause'], True, False, 0, 3], 3: [True, ['pause'], True, False, 0, 3], 4: [True, ['pause'], True, False, 0, 3], 5: [True, ['pause'], True, False, 0, 3]}[N])
check('1', solve([5,2,2,5,True]), {1: [False, ['resume'], False, True, 3, 0], 2: [False, ['resume'], False, True, 3, 0], 3: [False, ['resume'], False, True, 3, 0], 4: [False, ['resume'], False, True, 3, 0], 5: [False, ['resume'], False, True, 3, 0]}[N])
check('2', solve([5,6,2,5,False]), {1: [False, [], True, False, 0, 4], 2: [False, [], True, False, 0, 4], 3: [False, [], True, False, 0, 4], 4: [False, [], True, False, 0, 4], 5: [False, [], True, False, 0, 4]}[N])
check('3', solve([2,1,2,5,True]), {1: [True, [], False, True, 4, 0], 2: [True, [], False, True, 4, 0], 3: [True, [], False, True, 4, 0], 4: [True, [], False, True, 4, 0], 5: [True, [], False, True, 4, 0]}[N])
check('4', solve([N,N,0,N+3,False]), {1: [False, [], False, False, 3, 1], 2: [False, [], False, False, 3, 2], 3: [False, [], False, False, 3, 3], 4: [False, [], False, False, 3, 4], 5: [False, [], False, False, 3, 5]}[N])
check('5', solve([3,4,2,5,False]), {1: [False, [], False, False, 1, 2], 2: [False, [], False, False, 1, 2], 3: [False, [], False, False, 1, 2], 4: [False, [], False, False, 1, 2], 5: [False, [], False, False, 1, 2]}[N])
check('6', solve([6,1,2,5,True]), {1: [False, ['resume'], False, True, 4, 0], 2: [False, ['resume'], False, True, 4, 0], 3: [False, ['resume'], False, True, 4, 0], 4: [False, ['resume'], False, True, 4, 0], 5: [False, ['resume'], False, True, 4, 0]}[N])
check('7', solve([1,7,2,5,False]), {1: [True, ['pause'], True, False, 0, 5], 2: [True, ['pause'], True, False, 0, 5], 3: [True, ['pause'], True, False, 0, 5], 4: [True, ['pause'], True, False, 0, 5], 5: [True, ['pause'], True, False, 0, 5]}[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 | [True, ['pause'], False, False, 0, 3] | [True, ['pause'], True, False, 0, 3] | Failed |
| 1 | [False, ['resume'], False, True, 3, 0] | [False, ['resume'], False, True, 3, 0] | Passed |
| 2 | [False, [], True, False, 0, 4] | [False, [], True, False, 0, 4] | Passed |
| 3 | [True, [], False, True, 4, 0] | [True, [], False, True, 4, 0] | Passed |
| 4 | [False, [], False, False, 3, 1] | [False, [], False, False, 3, 1] | Passed |
| 5 | [False, [], False, False, 1, 2] | [False, [], False, False, 1, 2] | Passed |
| 6 | [False, ['resume'], False, True, 4, 0] | [False, ['resume'], False, True, 4, 0] | Passed |
| 7 | [True, ['pause'], True, False, 0, 5] | [True, ['pause'], True, False, 0, 5] | Passed |
SHA-256 / fcff36d7fc5a8cb1980670979c6545ea42c5383ab4cb17fae126cce97b48e4f8
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
old,new,low,high,paused=x
events=[]
state=paused
if not paused and old<high<=new:
state=True
events.append('pause')
if paused and old>low>=new:
state=False
events.append('resume')
at_high=new>high or (high==0 and new==0)
at_low=new<=low
headroom=max(0,high-new)
excess=max(0,new-low)
return [state,events,at_high,at_low,headroom,excess]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([2,5,2,5,False]), {1: [True, ['pause'], True, False, 0, 3], 2: [True, ['pause'], True, False, 0, 3], 3: [True, ['pause'], True, False, 0, 3], 4: [True, ['pause'], True, False, 0, 3], 5: [True, ['pause'], True, False, 0, 3]}[N])
check('1', solve([5,2,2,5,True]), {1: [False, ['resume'], False, True, 3, 0], 2: [False, ['resume'], False, True, 3, 0], 3: [False, ['resume'], False, True, 3, 0], 4: [False, ['resume'], False, True, 3, 0], 5: [False, ['resume'], False, True, 3, 0]}[N])
check('2', solve([5,6,2,5,False]), {1: [False, [], True, False, 0, 4], 2: [False, [], True, False, 0, 4], 3: [False, [], True, False, 0, 4], 4: [False, [], True, False, 0, 4], 5: [False, [], True, False, 0, 4]}[N])
check('3', solve([2,1,2,5,True]), {1: [True, [], False, True, 4, 0], 2: [True, [], False, True, 4, 0], 3: [True, [], False, True, 4, 0], 4: [True, [], False, True, 4, 0], 5: [True, [], False, True, 4, 0]}[N])
check('4', solve([N,N,0,N+3,False]), {1: [False, [], False, False, 3, 1], 2: [False, [], False, False, 3, 2], 3: [False, [], False, False, 3, 3], 4: [False, [], False, False, 3, 4], 5: [False, [], False, False, 3, 5]}[N])
check('5', solve([3,4,2,5,False]), {1: [False, [], False, False, 1, 2], 2: [False, [], False, False, 1, 2], 3: [False, [], False, False, 1, 2], 4: [False, [], False, False, 1, 2], 5: [False, [], False, False, 1, 2]}[N])
check('6', solve([6,1,2,5,True]), {1: [False, ['resume'], False, True, 4, 0], 2: [False, ['resume'], False, True, 4, 0], 3: [False, ['resume'], False, True, 4, 0], 4: [False, ['resume'], False, True, 4, 0], 5: [False, ['resume'], False, True, 4, 0]}[N])
check('7', solve([1,7,2,5,False]), {1: [True, ['pause'], True, False, 0, 5], 2: [True, ['pause'], True, False, 0, 5], 3: [True, ['pause'], True, False, 0, 5], 4: [True, ['pause'], True, False, 0, 5], 5: [True, ['pause'], True, False, 0, 5]}[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 | [True, ['pause'], False, False, 0, 3] | [True, ['pause'], True, False, 0, 3] | Failed |
| 1 | [False, ['resume'], False, True, 3, 0] | [False, ['resume'], False, True, 3, 0] | Passed |
| 2 | [False, [], True, False, 0, 4] | [False, [], True, False, 0, 4] | Passed |
| 3 | [True, [], False, True, 4, 0] | [True, [], False, True, 4, 0] | Passed |
| 4 | [False, [], False, False, 3, 1] | [False, [], False, False, 3, 1] | Passed |
| 5 | [False, [], False, False, 1, 2] | [False, [], False, False, 1, 2] | Passed |
| 6 | [False, ['resume'], False, True, 4, 0] | [False, ['resume'], False, True, 4, 0] | Passed |
| 7 | [True, ['pause'], True, False, 0, 5] | [True, ['pause'], True, False, 0, 5] | Passed |
SHA-256 / 53a5300f3547f28a318cfd6a58a072c1c42adf51a2da2abf71afccf21285e53e
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
old,new,low,high,paused=x
events=[]
state=paused
if not paused and old<high<=new:
state=True
events.append('pause')
if paused and old>low>=new:
state=False
events.append('resume')
at_high=new>=high
at_low=new<=low
headroom=max(0,high-new)
excess=max(0,new-low)
return [state,events,at_high,at_low,headroom,excess]
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([2,5,2,5,False]), {1: [True, ['pause'], True, False, 0, 3], 2: [True, ['pause'], True, False, 0, 3], 3: [True, ['pause'], True, False, 0, 3], 4: [True, ['pause'], True, False, 0, 3], 5: [True, ['pause'], True, False, 0, 3]}[N])
check('1', solve([5,2,2,5,True]), {1: [False, ['resume'], False, True, 3, 0], 2: [False, ['resume'], False, True, 3, 0], 3: [False, ['resume'], False, True, 3, 0], 4: [False, ['resume'], False, True, 3, 0], 5: [False, ['resume'], False, True, 3, 0]}[N])
check('2', solve([5,6,2,5,False]), {1: [False, [], True, False, 0, 4], 2: [False, [], True, False, 0, 4], 3: [False, [], True, False, 0, 4], 4: [False, [], True, False, 0, 4], 5: [False, [], True, False, 0, 4]}[N])
check('3', solve([2,1,2,5,True]), {1: [True, [], False, True, 4, 0], 2: [True, [], False, True, 4, 0], 3: [True, [], False, True, 4, 0], 4: [True, [], False, True, 4, 0], 5: [True, [], False, True, 4, 0]}[N])
check('4', solve([N,N,0,N+3,False]), {1: [False, [], False, False, 3, 1], 2: [False, [], False, False, 3, 2], 3: [False, [], False, False, 3, 3], 4: [False, [], False, False, 3, 4], 5: [False, [], False, False, 3, 5]}[N])
check('5', solve([3,4,2,5,False]), {1: [False, [], False, False, 1, 2], 2: [False, [], False, False, 1, 2], 3: [False, [], False, False, 1, 2], 4: [False, [], False, False, 1, 2], 5: [False, [], False, False, 1, 2]}[N])
check('6', solve([6,1,2,5,True]), {1: [False, ['resume'], False, True, 4, 0], 2: [False, ['resume'], False, True, 4, 0], 3: [False, ['resume'], False, True, 4, 0], 4: [False, ['resume'], False, True, 4, 0], 5: [False, ['resume'], False, True, 4, 0]}[N])
check('7', solve([1,7,2,5,False]), {1: [True, ['pause'], True, False, 0, 5], 2: [True, ['pause'], True, False, 0, 5], 3: [True, ['pause'], True, False, 0, 5], 4: [True, ['pause'], True, False, 0, 5], 5: [True, ['pause'], True, False, 0, 5]}[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 | [True, ['pause'], True, False, 0, 3] | [True, ['pause'], True, False, 0, 3] | Passed |
| 1 | [False, ['resume'], False, True, 3, 0] | [False, ['resume'], False, True, 3, 0] | Passed |
| 2 | [False, [], True, False, 0, 4] | [False, [], True, False, 0, 4] | Passed |
| 3 | [True, [], False, True, 4, 0] | [True, [], False, True, 4, 0] | Passed |
| 4 | [False, [], False, False, 3, 1] | [False, [], False, False, 3, 1] | Passed |
| 5 | [False, [], False, False, 1, 2] | [False, [], False, False, 1, 2] | Passed |
| 6 | [False, ['resume'], False, True, 4, 0] | [False, ['resume'], False, True, 4, 0] | Passed |
| 7 | [True, ['pause'], True, False, 0, 5] | [True, ['pause'], True, False, 0, 5] | Passed |
SHA-256 / b13ba957da5a5b080a055843a0651f082dfd204d40cd1e9825d77609620abcc9
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 2026-09-29T14:44:39.092080+00:00.
Case digest / fd6946ecc33ceaaf72e346bdd16669d512837d12a697f3fc9d4ab20e353370fe