FA-29641 / HTTP retries / Open access
Retry only unresolved batch members: An unsolicited result injects an item into the next retry batch · case 01
An unsolicited result injects an item into the next retry batch
ROOT CAUSE
An unsolicited result injects an item into the next retry batch
VERIFIED REPAIR
Restore the specified transition if k not in state: continue.
Unsuccessful approach: The attempted repair changes the faulty site to if k not in state: state[k]=['pending',None]; order.insert(0,k) but still violates a regression oracle.
Case contract
open(list of item IDs) establishes ordered batch. result(id,status,value) records first success, retryable failure, or permanent failure; unknown IDs ignored. retry returns unresolved/retryable items in original order including duplicates. done returns values or null in original positions. Success/permanent terminal entries cannot be overwritten by late responses.
Why this case matters
Offline deterministic model of HTTP request retries.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(events):
order=[]; state={}; out=[]
for e in events:
if e[0]=='open':
order=list(e[1]); state={k:['pending',None] for k in order}
elif e[0]=='result':
k,status,value=e[1:]
if k not in state: state[k]=['pending',None]; order.append(k)
if state[k][0] in ('success','permanent'): continue
if status=='success': state[k]=['success',value]
elif status=='permanent': state[k]=['permanent',None]
else: state[k]=['retry',None]
elif e[0]=='retry':
out.append([k for k in order if state[k][0] in ('pending','retry')])
elif e[0]=='done':
out.append([state[k][1] if state[k][0]=='success' else None for k in order])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([]), [])
check('1', solve([('open',['b','a','b']),('retry',),('result','b','success',N),('done',),('retry',)]), [['b','a','b'],[N,None,N],['a']])
check('2', solve([('open',['a','b']),('result','a','retry',N),('result','b','permanent',N),('retry',),('done',)]), [['a'],[None,None]])
check('3', solve([('open',['a']),('result','z','success',N),('retry',),('done',)]), [['a'],[None]])
check('4', solve([('open',['a','b']),('result','a','success',N),('result','a','retry',0),('result','b','permanent',0),('result','b','retry',0),('retry',),('done',)]), [[],[N,None]])
check('5', solve([('open',['a']),('result','a','success',N),('open',['a']),('retry',),('done',)]), [['a'],[None]])
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 | [] | [] | Passed |
| 1 | [['b', 'a', 'b'], [1, None, 1], ['a']] | [['b', 'a', 'b'], [1, None, 1], ['a']] | Passed |
| 2 | [['a'], [None, None]] | [['a'], [None, None]] | Passed |
| 3 | [['a'], [None, 1]] | [['a'], [None]] | Failed |
| 4 | [[], [1, None]] | [[], [1, None]] | Passed |
| 5 | [['a'], [None]] | [['a'], [None]] | Passed |
SHA-256 / 761ea51c472170fbb21878777690e5896eebc77f7d7b74b699a6d24621990d54
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(events):
order=[]; state={}; out=[]
for e in events:
if e[0]=='open':
order=list(e[1]); state={k:['pending',None] for k in order}
elif e[0]=='result':
k,status,value=e[1:]
if k not in state: state[k]=['pending',None]; order.insert(0,k)
if state[k][0] in ('success','permanent'): continue
if status=='success': state[k]=['success',value]
elif status=='permanent': state[k]=['permanent',None]
else: state[k]=['retry',None]
elif e[0]=='retry':
out.append([k for k in order if state[k][0] in ('pending','retry')])
elif e[0]=='done':
out.append([state[k][1] if state[k][0]=='success' else None for k in order])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([]), [])
check('1', solve([('open',['b','a','b']),('retry',),('result','b','success',N),('done',),('retry',)]), [['b','a','b'],[N,None,N],['a']])
check('2', solve([('open',['a','b']),('result','a','retry',N),('result','b','permanent',N),('retry',),('done',)]), [['a'],[None,None]])
check('3', solve([('open',['a']),('result','z','success',N),('retry',),('done',)]), [['a'],[None]])
check('4', solve([('open',['a','b']),('result','a','success',N),('result','a','retry',0),('result','b','permanent',0),('result','b','retry',0),('retry',),('done',)]), [[],[N,None]])
check('5', solve([('open',['a']),('result','a','success',N),('open',['a']),('retry',),('done',)]), [['a'],[None]])
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 | [] | [] | Passed |
| 1 | [['b', 'a', 'b'], [1, None, 1], ['a']] | [['b', 'a', 'b'], [1, None, 1], ['a']] | Passed |
| 2 | [['a'], [None, None]] | [['a'], [None, None]] | Passed |
| 3 | [['a'], [1, None]] | [['a'], [None]] | Failed |
| 4 | [[], [1, None]] | [[], [1, None]] | Passed |
| 5 | [['a'], [None]] | [['a'], [None]] | Passed |
SHA-256 / 68aaf8aaa833167cd3d0d7782c35c7c9393cf233eb25432a6e933eabf06a3578
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(events):
order=[]; state={}; out=[]
for e in events:
if e[0]=='open':
order=list(e[1]); state={k:['pending',None] for k in order}
elif e[0]=='result':
k,status,value=e[1:]
if k not in state: continue
if state[k][0] in ('success','permanent'): continue
if status=='success': state[k]=['success',value]
elif status=='permanent': state[k]=['permanent',None]
else: state[k]=['retry',None]
elif e[0]=='retry':
out.append([k for k in order if state[k][0] in ('pending','retry')])
elif e[0]=='done':
out.append([state[k][1] if state[k][0]=='success' else None for k in order])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('0', solve([]), [])
check('1', solve([('open',['b','a','b']),('retry',),('result','b','success',N),('done',),('retry',)]), [['b','a','b'],[N,None,N],['a']])
check('2', solve([('open',['a','b']),('result','a','retry',N),('result','b','permanent',N),('retry',),('done',)]), [['a'],[None,None]])
check('3', solve([('open',['a']),('result','z','success',N),('retry',),('done',)]), [['a'],[None]])
check('4', solve([('open',['a','b']),('result','a','success',N),('result','a','retry',0),('result','b','permanent',0),('result','b','retry',0),('retry',),('done',)]), [[],[N,None]])
check('5', solve([('open',['a']),('result','a','success',N),('open',['a']),('retry',),('done',)]), [['a'],[None]])
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 | [] | [] | Passed |
| 1 | [['b', 'a', 'b'], [1, None, 1], ['a']] | [['b', 'a', 'b'], [1, None, 1], ['a']] | Passed |
| 2 | [['a'], [None, None]] | [['a'], [None, None]] | Passed |
| 3 | [['a'], [None]] | [['a'], [None]] | Passed |
| 4 | [[], [1, None]] | [[], [1, None]] | Passed |
| 5 | [['a'], [None]] | [['a'], [None]] | Passed |
SHA-256 / b8a1435b2101cfd498dd8d0e1223e1a11ed44f7cc94d880177a1e3743b2ec5ea
Verification & scope
Stipulated bounded simulator, not a complete HTTP implementation or a standards conformance claim. 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 2026-09-29T14:41:45.112925+00:00.
Case digest / b6ec36c4db91b24fa896669c78efad5f27cce86d86fd4fa401f78079f0271ba0