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FA-44416 / Data systems / Open access

Run validity is addressed by the slice-local row · case 01

Run validity is addressed by the slice-local row.

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

ROOT CAUSE

run-end-slice: Run validity is addressed by the slice-local row.

THE FAILURE

run-end-slice: Run validity is addressed by the slice-local row.

Unsuccessful approach: Intersecting with the first run makes its nullness leak into later runs.

Case contract

Decode a run-end vector into the requested [start,start+length) slice. Run ends are exclusive cumulative positions; values and validity are stored per run. Empty slices return empty.

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:
        ends,values,valid,start,length=d
        out=[]
        for pos in range(start,start+length):
            r=next(i for i,end in enumerate(ends) if pos < end)
            value=values[r]
            known=valid[min(pos-start,len(valid)-1)]
            out.append(value if known else None)
        return out
    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('crossing run boundary', solve([[2, 5], [1, 2], [True, True], 1, 3]), [1, 2, 2])
    check('start at boundary', solve([[2, 5], [1, 2], [True, True], 2, 2]), [2, 2])
    check('null middle run', solve([[1, 3, 5], [1, 2, 3], [True, False, True], 0, 5]), [1, None, None, 3, 3])
    check('null first run', solve([[1, 3], [1, 2], [False, True], 1, 2]), [2, 2])
    check('empty slice', solve([[3], [1], [True], 1, 0]), [])
    check('single run', solve([[4], [1], [True], 0, 4]), [1, 1, 1, 1])
    check('tail slice', solve([[1, 2, 6], [1, 2, 3], [True, True, True], 4, 2]), [3, 3])
elif N == 2:
    check('crossing run boundary', solve([[2, 5], [2, 3], [True, True], 1, 3]), [2, 3, 3])
    check('start at boundary', solve([[2, 5], [2, 3], [True, True], 2, 2]), [3, 3])
    check('null middle run', solve([[1, 3, 5], [2, 3, 4], [True, False, True], 0, 5]), [2, None, None, 4, 4])
    check('null first run', solve([[1, 3], [2, 3], [False, True], 1, 2]), [3, 3])
    check('empty slice', solve([[3], [2], [True], 1, 0]), [])
    check('single run', solve([[4], [2], [True], 0, 4]), [2, 2, 2, 2])
    check('tail slice', solve([[1, 2, 6], [2, 3, 4], [True, True, True], 4, 2]), [4, 4])
elif N == 3:
    check('crossing run boundary', solve([[2, 5], [3, 4], [True, True], 1, 3]), [3, 4, 4])
    check('start at boundary', solve([[2, 5], [3, 4], [True, True], 2, 2]), [4, 4])
    check('null middle run', solve([[1, 3, 5], [3, 4, 5], [True, False, True], 0, 5]), [3, None, None, 5, 5])
    check('null first run', solve([[1, 3], [3, 4], [False, True], 1, 2]), [4, 4])
    check('empty slice', solve([[3], [3], [True], 1, 0]), [])
    check('single run', solve([[4], [3], [True], 0, 4]), [3, 3, 3, 3])
    check('tail slice', solve([[1, 2, 6], [3, 4, 5], [True, True, True], 4, 2]), [5, 5])
elif N == 4:
    check('crossing run boundary', solve([[2, 5], [4, 5], [True, True], 1, 3]), [4, 5, 5])
    check('start at boundary', solve([[2, 5], [4, 5], [True, True], 2, 2]), [5, 5])
    check('null middle run', solve([[1, 3, 5], [4, 5, 6], [True, False, True], 0, 5]), [4, None, None, 6, 6])
    check('null first run', solve([[1, 3], [4, 5], [False, True], 1, 2]), [5, 5])
    check('empty slice', solve([[3], [4], [True], 1, 0]), [])
    check('single run', solve([[4], [4], [True], 0, 4]), [4, 4, 4, 4])
    check('tail slice', solve([[1, 2, 6], [4, 5, 6], [True, True, True], 4, 2]), [6, 6])
elif N == 5:
    check('crossing run boundary', solve([[2, 5], [5, 6], [True, True], 1, 3]), [5, 6, 6])
    check('start at boundary', solve([[2, 5], [5, 6], [True, True], 2, 2]), [6, 6])
    check('null middle run', solve([[1, 3, 5], [5, 6, 7], [True, False, True], 0, 5]), [5, None, None, 7, 7])
    check('null first run', solve([[1, 3], [5, 6], [False, True], 1, 2]), [6, 6])
    check('empty slice', solve([[3], [5], [True], 1, 0]), [])
    check('single run', solve([[4], [5], [True], 0, 4]), [5, 5, 5, 5])
    check('tail slice', solve([[1, 2, 6], [5, 6, 7], [True, True, True], 4, 2]), [7, 7])
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
crossing run boundary[1, 2, 2][1, 2, 2]Passed
start at boundary[2, 2][2, 2]Passed
null middle run[1, None, 2, 3, 3][1, None, None, 3, 3]Failed
null first run[None, 2][2, 2]Failed
empty slice[][]Passed
single run[1, 1, 1, 1][1, 1, 1, 1]Passed
tail slice[3, 3][3, 3]Passed

SHA-256 / 38ef374119d0105f7c2814322ed8889b99ac2e87c3d2ff0d5345a8547c563494

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(d):
    try:
        ends,values,valid,start,length=d
        out=[]
        for pos in range(start,start+length):
            r=next(i for i,end in enumerate(ends) if pos < end)
            value=values[r]
            known=valid[r] and valid[0]
            out.append(value if known else None)
        return out
    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('crossing run boundary', solve([[2, 5], [1, 2], [True, True], 1, 3]), [1, 2, 2])
    check('start at boundary', solve([[2, 5], [1, 2], [True, True], 2, 2]), [2, 2])
    check('null middle run', solve([[1, 3, 5], [1, 2, 3], [True, False, True], 0, 5]), [1, None, None, 3, 3])
    check('null first run', solve([[1, 3], [1, 2], [False, True], 1, 2]), [2, 2])
    check('empty slice', solve([[3], [1], [True], 1, 0]), [])
    check('single run', solve([[4], [1], [True], 0, 4]), [1, 1, 1, 1])
    check('tail slice', solve([[1, 2, 6], [1, 2, 3], [True, True, True], 4, 2]), [3, 3])
elif N == 2:
    check('crossing run boundary', solve([[2, 5], [2, 3], [True, True], 1, 3]), [2, 3, 3])
    check('start at boundary', solve([[2, 5], [2, 3], [True, True], 2, 2]), [3, 3])
    check('null middle run', solve([[1, 3, 5], [2, 3, 4], [True, False, True], 0, 5]), [2, None, None, 4, 4])
    check('null first run', solve([[1, 3], [2, 3], [False, True], 1, 2]), [3, 3])
    check('empty slice', solve([[3], [2], [True], 1, 0]), [])
    check('single run', solve([[4], [2], [True], 0, 4]), [2, 2, 2, 2])
    check('tail slice', solve([[1, 2, 6], [2, 3, 4], [True, True, True], 4, 2]), [4, 4])
elif N == 3:
    check('crossing run boundary', solve([[2, 5], [3, 4], [True, True], 1, 3]), [3, 4, 4])
    check('start at boundary', solve([[2, 5], [3, 4], [True, True], 2, 2]), [4, 4])
    check('null middle run', solve([[1, 3, 5], [3, 4, 5], [True, False, True], 0, 5]), [3, None, None, 5, 5])
    check('null first run', solve([[1, 3], [3, 4], [False, True], 1, 2]), [4, 4])
    check('empty slice', solve([[3], [3], [True], 1, 0]), [])
    check('single run', solve([[4], [3], [True], 0, 4]), [3, 3, 3, 3])
    check('tail slice', solve([[1, 2, 6], [3, 4, 5], [True, True, True], 4, 2]), [5, 5])
elif N == 4:
    check('crossing run boundary', solve([[2, 5], [4, 5], [True, True], 1, 3]), [4, 5, 5])
    check('start at boundary', solve([[2, 5], [4, 5], [True, True], 2, 2]), [5, 5])
    check('null middle run', solve([[1, 3, 5], [4, 5, 6], [True, False, True], 0, 5]), [4, None, None, 6, 6])
    check('null first run', solve([[1, 3], [4, 5], [False, True], 1, 2]), [5, 5])
    check('empty slice', solve([[3], [4], [True], 1, 0]), [])
    check('single run', solve([[4], [4], [True], 0, 4]), [4, 4, 4, 4])
    check('tail slice', solve([[1, 2, 6], [4, 5, 6], [True, True, True], 4, 2]), [6, 6])
elif N == 5:
    check('crossing run boundary', solve([[2, 5], [5, 6], [True, True], 1, 3]), [5, 6, 6])
    check('start at boundary', solve([[2, 5], [5, 6], [True, True], 2, 2]), [6, 6])
    check('null middle run', solve([[1, 3, 5], [5, 6, 7], [True, False, True], 0, 5]), [5, None, None, 7, 7])
    check('null first run', solve([[1, 3], [5, 6], [False, True], 1, 2]), [6, 6])
    check('empty slice', solve([[3], [5], [True], 1, 0]), [])
    check('single run', solve([[4], [5], [True], 0, 4]), [5, 5, 5, 5])
    check('tail slice', solve([[1, 2, 6], [5, 6, 7], [True, True, True], 4, 2]), [7, 7])
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
crossing run boundary[1, 2, 2][1, 2, 2]Passed
start at boundary[2, 2][2, 2]Passed
null middle run[1, None, None, 3, 3][1, None, None, 3, 3]Passed
null first run[None, None][2, 2]Failed
empty slice[][]Passed
single run[1, 1, 1, 1][1, 1, 1, 1]Passed
tail slice[3, 3][3, 3]Passed

SHA-256 / cbdedb99eebdf643547bf46524cf9d832fb4f92d2766459e08579519086b993a

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 2026-09-29T14:44:12.113188+00:00.

Case digest / 85d642d5836276ed02fd62fbfa05aed19f02be841afbddc23ad5b7bc30a1f27b