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FA-44531 / Data systems / Open access

Chunked row assembly reverses column positions · case 01

Chunked row assembly reverses column positions.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

chunked-column-zip: Chunked row assembly reverses column positions.

THE FAILURE

chunked-column-zip: Chunked row assembly reverses column positions.

Unsuccessful approach: Correcting column order while reversing right-side row addresses remains misaligned.

Case contract

Assemble two equally long logical columns from independent chunk layouts. Empty chunks carry no rows. Zip by global row ordinal, retain null values, and apply the requested half-open row slice after alignment.

Why this case matters

A bounded deterministic data engine model makes representation and changelog faults reproducible.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(d):
    try:
        left,right,start,length=d
        a=[v for chunk in left for v in chunk]
        b=[v for chunk in right for v in chunk]
        rows=[[b[i],a[i]] for i in range(len(a))]
        rows=rows[start:start+length]
        return rows
    except (IndexError, KeyError, ValueError, StopIteration) as exc:
        return {"representation_error": type(exc).__name__}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
if N == 1:
    check('different boundaries', solve([[[1, 2], [3]], [[4], [5, 6]], 0, 3]), [[1, 4], [2, 5], [3, 6]])
    check('empty internal chunks', solve([[[1], [], [2]], [[], [3, 4]], 0, 2]), [[1, 3], [2, 4]])
    check('global slice', solve([[[1], [2, 3]], [[4, 5], [6]], 1, 2]), [[2, 5], [3, 6]])
    check('null field', solve([[[None, 1]], [[2, None]], 0, 2]), [[None, 2], [1, None]])
    check('repeated rows', solve([[[1, 1]], [[2, 2]], 0, 2]), [[1, 2], [1, 2]])
    check('zero length', solve([[[1]], [[2]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 2:
    check('different boundaries', solve([[[2, 3], [4]], [[5], [6, 7]], 0, 3]), [[2, 5], [3, 6], [4, 7]])
    check('empty internal chunks', solve([[[2], [], [3]], [[], [4, 5]], 0, 2]), [[2, 4], [3, 5]])
    check('global slice', solve([[[2], [3, 4]], [[5, 6], [7]], 1, 2]), [[3, 6], [4, 7]])
    check('null field', solve([[[None, 2]], [[3, None]], 0, 2]), [[None, 3], [2, None]])
    check('repeated rows', solve([[[2, 2]], [[3, 3]], 0, 2]), [[2, 3], [2, 3]])
    check('zero length', solve([[[2]], [[3]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 3:
    check('different boundaries', solve([[[3, 4], [5]], [[6], [7, 8]], 0, 3]), [[3, 6], [4, 7], [5, 8]])
    check('empty internal chunks', solve([[[3], [], [4]], [[], [5, 6]], 0, 2]), [[3, 5], [4, 6]])
    check('global slice', solve([[[3], [4, 5]], [[6, 7], [8]], 1, 2]), [[4, 7], [5, 8]])
    check('null field', solve([[[None, 3]], [[4, None]], 0, 2]), [[None, 4], [3, None]])
    check('repeated rows', solve([[[3, 3]], [[4, 4]], 0, 2]), [[3, 4], [3, 4]])
    check('zero length', solve([[[3]], [[4]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 4:
    check('different boundaries', solve([[[4, 5], [6]], [[7], [8, 9]], 0, 3]), [[4, 7], [5, 8], [6, 9]])
    check('empty internal chunks', solve([[[4], [], [5]], [[], [6, 7]], 0, 2]), [[4, 6], [5, 7]])
    check('global slice', solve([[[4], [5, 6]], [[7, 8], [9]], 1, 2]), [[5, 8], [6, 9]])
    check('null field', solve([[[None, 4]], [[5, None]], 0, 2]), [[None, 5], [4, None]])
    check('repeated rows', solve([[[4, 4]], [[5, 5]], 0, 2]), [[4, 5], [4, 5]])
    check('zero length', solve([[[4]], [[5]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 5:
    check('different boundaries', solve([[[5, 6], [7]], [[8], [9, 10]], 0, 3]), [[5, 8], [6, 9], [7, 10]])
    check('empty internal chunks', solve([[[5], [], [6]], [[], [7, 8]], 0, 2]), [[5, 7], [6, 8]])
    check('global slice', solve([[[5], [6, 7]], [[8, 9], [10]], 1, 2]), [[6, 9], [7, 10]])
    check('null field', solve([[[None, 5]], [[6, None]], 0, 2]), [[None, 6], [5, None]])
    check('repeated rows', solve([[[5, 5]], [[6, 6]], 0, 2]), [[5, 6], [5, 6]])
    check('zero length', solve([[[5]], [[6]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
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 fixtureActualExpectedOutcome
different boundaries[[4, 1], [5, 2], [6, 3]][[1, 4], [2, 5], [3, 6]]Failed
empty internal chunks[[3, 1], [4, 2]][[1, 3], [2, 4]]Failed
global slice[[5, 2], [6, 3]][[2, 5], [3, 6]]Failed
null field[[2, None], [None, 1]][[None, 2], [1, None]]Failed
repeated rows[[2, 1], [2, 1]][[1, 2], [1, 2]]Failed
zero length[][]Passed
no physical chunks[][]Passed

SHA-256 / 432a2400142d9b1046ac03051131d9024fc6c22653c3ef4fa28b6740896b820f

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(d):
    try:
        left,right,start,length=d
        a=[v for chunk in left for v in chunk]
        b=[v for chunk in right for v in chunk]
        rows=[[a[i],b[-i-1]] for i in range(len(a))]
        rows=rows[start:start+length]
        return rows
    except (IndexError, KeyError, ValueError, StopIteration) as exc:
        return {"representation_error": type(exc).__name__}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
if N == 1:
    check('different boundaries', solve([[[1, 2], [3]], [[4], [5, 6]], 0, 3]), [[1, 4], [2, 5], [3, 6]])
    check('empty internal chunks', solve([[[1], [], [2]], [[], [3, 4]], 0, 2]), [[1, 3], [2, 4]])
    check('global slice', solve([[[1], [2, 3]], [[4, 5], [6]], 1, 2]), [[2, 5], [3, 6]])
    check('null field', solve([[[None, 1]], [[2, None]], 0, 2]), [[None, 2], [1, None]])
    check('repeated rows', solve([[[1, 1]], [[2, 2]], 0, 2]), [[1, 2], [1, 2]])
    check('zero length', solve([[[1]], [[2]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 2:
    check('different boundaries', solve([[[2, 3], [4]], [[5], [6, 7]], 0, 3]), [[2, 5], [3, 6], [4, 7]])
    check('empty internal chunks', solve([[[2], [], [3]], [[], [4, 5]], 0, 2]), [[2, 4], [3, 5]])
    check('global slice', solve([[[2], [3, 4]], [[5, 6], [7]], 1, 2]), [[3, 6], [4, 7]])
    check('null field', solve([[[None, 2]], [[3, None]], 0, 2]), [[None, 3], [2, None]])
    check('repeated rows', solve([[[2, 2]], [[3, 3]], 0, 2]), [[2, 3], [2, 3]])
    check('zero length', solve([[[2]], [[3]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 3:
    check('different boundaries', solve([[[3, 4], [5]], [[6], [7, 8]], 0, 3]), [[3, 6], [4, 7], [5, 8]])
    check('empty internal chunks', solve([[[3], [], [4]], [[], [5, 6]], 0, 2]), [[3, 5], [4, 6]])
    check('global slice', solve([[[3], [4, 5]], [[6, 7], [8]], 1, 2]), [[4, 7], [5, 8]])
    check('null field', solve([[[None, 3]], [[4, None]], 0, 2]), [[None, 4], [3, None]])
    check('repeated rows', solve([[[3, 3]], [[4, 4]], 0, 2]), [[3, 4], [3, 4]])
    check('zero length', solve([[[3]], [[4]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 4:
    check('different boundaries', solve([[[4, 5], [6]], [[7], [8, 9]], 0, 3]), [[4, 7], [5, 8], [6, 9]])
    check('empty internal chunks', solve([[[4], [], [5]], [[], [6, 7]], 0, 2]), [[4, 6], [5, 7]])
    check('global slice', solve([[[4], [5, 6]], [[7, 8], [9]], 1, 2]), [[5, 8], [6, 9]])
    check('null field', solve([[[None, 4]], [[5, None]], 0, 2]), [[None, 5], [4, None]])
    check('repeated rows', solve([[[4, 4]], [[5, 5]], 0, 2]), [[4, 5], [4, 5]])
    check('zero length', solve([[[4]], [[5]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
elif N == 5:
    check('different boundaries', solve([[[5, 6], [7]], [[8], [9, 10]], 0, 3]), [[5, 8], [6, 9], [7, 10]])
    check('empty internal chunks', solve([[[5], [], [6]], [[], [7, 8]], 0, 2]), [[5, 7], [6, 8]])
    check('global slice', solve([[[5], [6, 7]], [[8, 9], [10]], 1, 2]), [[6, 9], [7, 10]])
    check('null field', solve([[[None, 5]], [[6, None]], 0, 2]), [[None, 6], [5, None]])
    check('repeated rows', solve([[[5, 5]], [[6, 6]], 0, 2]), [[5, 6], [5, 6]])
    check('zero length', solve([[[5]], [[6]], 0, 0]), [])
    check('no physical chunks', solve([[], [], 0, 0]), [])
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 fixtureActualExpectedOutcome
different boundaries[[1, 6], [2, 5], [3, 4]][[1, 4], [2, 5], [3, 6]]Failed
empty internal chunks[[1, 4], [2, 3]][[1, 3], [2, 4]]Failed
global slice[[2, 5], [3, 4]][[2, 5], [3, 6]]Failed
null field[[None, None], [1, 2]][[None, 2], [1, None]]Failed
repeated rows[[1, 2], [1, 2]][[1, 2], [1, 2]]Passed
zero length[][]Passed
no physical chunks[][]Passed

SHA-256 / ff99f71407e1a5434e9f97f2b90814025312912fffe7b9c1b06751601eeb77d0

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 7 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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Verification & scope

Offline stipulated semantics over valid small inputs; no performance, concurrency, or production-engine 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 2026-09-29T14:44:13.200582+00:00.

Case digest / 83c9d7b4242ed8ceef45d24de0767e77abc7d201ad41fff92beb796e3ed2dd12