FA-48536 / Delimited text / Open access

Later map entries silently replace an earlier named value · case 01

A structured table violates the declared record or column contract.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Later map entries silently replace an earlier named value.

VERIFIED REPAIR

Preserve the named invariant at the faulty decision: or parts[0] in mapping

Unsuccessful approach: The alternate implementation still violates the same declared invariant: later map entries silently replace an earlier named value.

Case contract

Decode a semicolon-delimited row of map cells enclosed in braces. Inside a map, comma separates entries and first equals separates key and value. Empty braces represent an empty map; empty values are legal, empty or duplicate keys reject. Ordinary scalar cells remain text, even with equals.

Why this case matters

Delimited interchange needs explicit framing, schema and field semantics at ingestion and emission boundaries.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
def _vary(value):
    if value == '@END': return 3 + 4*N
    if isinstance(value, str): return value.replace('@', 'cell' * N)
    if isinstance(value, list): return [_vary(x) for x in value]
    if isinstance(value, dict): return {_vary(k): _vary(v) for k,v in value.items()}
    return value
N = 1
observations = []
def solve(data):
    out=[]
    for cell in data.split(';'):
        if cell.startswith('{'):
            if not cell.endswith('}'): return None
            inner=cell[1:-1]; mapping={}
            for pair in inner.split(',') if inner else []:
                parts=pair.split('=',1)
                if len(parts)!=2 or not parts[0] : return None
                mapping[parts[0]]=parts[1]
            out.append(mapping)
        else:
            if '{' in cell or '}' in cell: return None
            out.append(cell)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('mixed', solve(_vary('@;{a=x,b=y}')), _vary(['@', {'a': 'x', 'b': 'y'}]))
check('empty', solve(_vary('{}')), _vary([{}]))
check('equals value', solve(_vary('{a=x=y}')), _vary([{'a': 'x=y'}]))
check('empty value', solve(_vary('{a=}')), _vary([{'a': ''}]))
check('duplicate', solve(_vary('{a=x,a=y}')), _vary(None))
check('empty key', solve(_vary('{=x}')), _vary(None))
check('scalar equals', solve(_vary('a=x')), _vary(['a=x']))
check('two maps', solve(_vary('{a=@};{a=z}')), _vary([{'a': '@'}, {'a': 'z'}]))
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
mixed	`['cell', {'a': 'x', 'b': 'y'}]`	`['cell', {'a': 'x', 'b': 'y'}]`	Passed
empty	`[{}]`	`[{}]`	Passed
equals value	`[{'a': 'x=y'}]`	`[{'a': 'x=y'}]`	Passed
empty value	`[{'a': ''}]`	`[{'a': ''}]`	Passed
duplicate	`[{'a': 'y'}]`	`None`	Failed
empty key	`None`	`None`	Passed
scalar equals	`['a=x']`	`['a=x']`	Passed
two maps	`[{'a': 'cell'}, {'a': 'z'}]`	`[{'a': 'cell'}, {'a': 'z'}]`	Passed

SHA-256 / 21004511cc577aaa4ec4dc956a37c09b3bdba0aef274250dd267656dc7ecc665

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
def _vary(value):
    if value == '@END': return 3 + 4*N
    if isinstance(value, str): return value.replace('@', 'cell' * N)
    if isinstance(value, list): return [_vary(x) for x in value]
    if isinstance(value, dict): return {_vary(k): _vary(v) for k,v in value.items()}
    return value
N = 1
observations = []
def solve(data):
    out=[]
    for cell in data.split(';'):
        if cell.startswith('{'):
            if not cell.endswith('}'): return None
            inner=cell[1:-1]; mapping={}
            for pair in inner.split(',') if inner else []:
                parts=pair.split('=',1)
                if len(parts)!=2 or not parts[0] or (parts[0] in mapping and mapping[parts[0]]==parts[1]): return None
                mapping[parts[0]]=parts[1]
            out.append(mapping)
        else:
            if '{' in cell or '}' in cell: return None
            out.append(cell)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('mixed', solve(_vary('@;{a=x,b=y}')), _vary(['@', {'a': 'x', 'b': 'y'}]))
check('empty', solve(_vary('{}')), _vary([{}]))
check('equals value', solve(_vary('{a=x=y}')), _vary([{'a': 'x=y'}]))
check('empty value', solve(_vary('{a=}')), _vary([{'a': ''}]))
check('duplicate', solve(_vary('{a=x,a=y}')), _vary(None))
check('empty key', solve(_vary('{=x}')), _vary(None))
check('scalar equals', solve(_vary('a=x')), _vary(['a=x']))
check('two maps', solve(_vary('{a=@};{a=z}')), _vary([{'a': '@'}, {'a': 'z'}]))
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
mixed	`['cell', {'a': 'x', 'b': 'y'}]`	`['cell', {'a': 'x', 'b': 'y'}]`	Passed
empty	`[{}]`	`[{}]`	Passed
equals value	`[{'a': 'x=y'}]`	`[{'a': 'x=y'}]`	Passed
empty value	`[{'a': ''}]`	`[{'a': ''}]`	Passed
duplicate	`[{'a': 'y'}]`	`None`	Failed
empty key	`None`	`None`	Passed
scalar equals	`['a=x']`	`['a=x']`	Passed
two maps	`[{'a': 'cell'}, {'a': 'z'}]`	`[{'a': 'cell'}, {'a': 'z'}]`	Passed

SHA-256 / feca63a2c597622ae04a7ada3ec5eeaae97e2fff2b1d83f078b58a68b449ec32

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
def _vary(value):
    if value == '@END': return 3 + 4*N
    if isinstance(value, str): return value.replace('@', 'cell' * N)
    if isinstance(value, list): return [_vary(x) for x in value]
    if isinstance(value, dict): return {_vary(k): _vary(v) for k,v in value.items()}
    return value
N = 1
observations = []
def solve(data):
    out=[]
    for cell in data.split(';'):
        if cell.startswith('{'):
            if not cell.endswith('}'): return None
            inner=cell[1:-1]; mapping={}
            for pair in inner.split(',') if inner else []:
                parts=pair.split('=',1)
                if len(parts)!=2 or not parts[0] or parts[0] in mapping: return None
                mapping[parts[0]]=parts[1]
            out.append(mapping)
        else:
            if '{' in cell or '}' in cell: return None
            out.append(cell)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('mixed', solve(_vary('@;{a=x,b=y}')), _vary(['@', {'a': 'x', 'b': 'y'}]))
check('empty', solve(_vary('{}')), _vary([{}]))
check('equals value', solve(_vary('{a=x=y}')), _vary([{'a': 'x=y'}]))
check('empty value', solve(_vary('{a=}')), _vary([{'a': ''}]))
check('duplicate', solve(_vary('{a=x,a=y}')), _vary(None))
check('empty key', solve(_vary('{=x}')), _vary(None))
check('scalar equals', solve(_vary('a=x')), _vary(['a=x']))
check('two maps', solve(_vary('{a=@};{a=z}')), _vary([{'a': '@'}, {'a': 'z'}]))
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
mixed	`['cell', {'a': 'x', 'b': 'y'}]`	`['cell', {'a': 'x', 'b': 'y'}]`	Passed
empty	`[{}]`	`[{}]`	Passed
equals value	`[{'a': 'x=y'}]`	`[{'a': 'x=y'}]`	Passed
empty value	`[{'a': ''}]`	`[{'a': ''}]`	Passed
duplicate	`None`	`None`	Passed
empty key	`None`	`None`	Passed
scalar equals	`['a=x']`	`['a=x']`	Passed
two maps	`[{'a': 'cell'}, {'a': 'z'}]`	`[{'a': 'cell'}, {'a': 'z'}]`	Passed

SHA-256 / 8c44ae1fdb3dae1cb9afe1c90d4a8d6e4a548a595041ee0b39d61c5e4f1131d1

Verification & scope

Deterministic bounded in-memory model. No claim of complete CSV or external format 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 2026-09-29T14:44:51.598319+00:00.

Case digest / 0ce796993c8d7c51d49059cb4a81c1c3aea42d1dc465dea93f46476aa7c0179a