FAILURE MAP
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FA-71881 / Error-correcting codes / Open access

SECDED flips the bit before the syndrome position · case 01

Single-bit errors are moved rather than corrected.

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

ROOT CAUSE

The correction uses c[s - 1], forgetting that index 0 holds the overall parity bit.

VERIFIED REPAIR

Flip c[s]; s = 0 refers to the overall parity bit at index 0.

Unsuccessful approach: Clamping the index at 0 still shifts every other correction.

Case contract

Extended Hamming (8,4) SECDED decoder. r[0] is the overall parity bit; r[1..7] are Hamming positions 1..7 with data at 3, 5, 6, 7. s is the XOR of set positions 1..7 and p the parity of all eight bits. s=0,p=0: "clean"; p=1: single error at position s (s=0 means the overall parity bit) - "corrected"; s!=0,p=0: ["double", None]. Return [status, data]. Non-binary or wrong-length input returns None.

Why this case matters

ECC DRAM controllers must distinguish correctable single-bit errors from uncorrectable double-bit errors.

1 / The failure

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

N = 1
observations = []
def solve(r):
    if len(r) != 8 or any(b not in (0, 1) for b in r):
        return None
    s = 0
    for pos in range(1, 8):
        if r[pos]:
            s ^= pos
    p = sum(r) % 2
    c = list(r)
    if s == 0 and p == 0:
        status = 'clean'
    elif p == 1:
        status = 'corrected'
        c[s - 1] ^= 1
    else:
        return ['double', None]
    return [status, [c[3], c[5], c[6], c[7]]]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression [[0, 1, 1, 0, 1, 1, 0, 1]]', [[0, 1, 1, 0, 1, 1, 0, 1]], ['corrected', [0, 0, 0, 1]]], ['regression [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['control [[0, 0, 0, 0, 0, 0, 0, 0]]', [[0, 0, 0, 0, 0, 0, 0, 0]], ['clean', [0, 0, 0, 0]]], ['control [[0, 1, 0, 0, 0, 0, 0, 0]]', [[0, 1, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 0, 0, 0, 0, 0, 1, 1]]', [[0, 0, 0, 0, 0, 0, 1, 1]], ['double', None]], ['control [[0, 1, 1, 0, 1, 0, 0, 1]]', [[0, 1, 1, 0, 1, 0, 0, 1]], ['clean', [0, 0, 0, 1]]], ['control [[0, 1, 0, 1, 1, 0, 0, 1]]', [[0, 1, 0, 1, 1, 0, 0, 1]], ['double', None]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]]], [['regression [[0, 1, 1, 0, 0, 0, 1, 0]]', [[0, 1, 1, 0, 0, 0, 1, 0]], ['corrected', [0, 1, 1, 0]]], ['regression [[0, 0, 0, 0, 1, 1, 1, 0]]', [[0, 0, 0, 0, 1, 1, 1, 0]], ['corrected', [0, 1, 1, 1]]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]], ['control [[1, 0, 0, 1, 1, 0, 1, 0]]', [[1, 0, 0, 1, 1, 0, 1, 0]], ['double', None]], ['control [[1, 1, 0, 0, 0, 0, 1, 1]]', [[1, 1, 0, 0, 0, 0, 1, 1]], ['clean', [0, 0, 1, 1]]], ['control [[1, 1, 1, 0, 0, 0, 1, 1]]', [[1, 1, 1, 0, 0, 0, 1, 1]], ['corrected', [0, 0, 1, 1]]], ['control [[1, 1, 0, 1, 0, 0, 0, 1]]', [[1, 1, 0, 1, 0, 0, 0, 1]], ['double', None]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]]], [['regression [[1, 0, 0, 1, 1, 0, 0, 0]]', [[1, 0, 0, 1, 1, 0, 0, 0]], ['corrected', [1, 0, 0, 1]]], ['regression [[0, 1, 0, 0, 1, 0, 1, 0]]', [[0, 1, 0, 0, 1, 0, 1, 0]], ['corrected', [1, 0, 1, 0]]], ['partial-repair [[0, 0, 1, 1, 0, 1, 1, 1]]', [[0, 0, 1, 1, 0, 1, 1, 1]], ['corrected', [1, 0, 1, 1]]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]], ['control [[1, 1, 1, 0, 1, 1, 0, 0]]', [[1, 1, 1, 0, 1, 1, 0, 0]], ['corrected', [0, 1, 0, 0]]], ['control [[1, 0, 0, 0, 1, 0, 0, 0]]', [[1, 0, 0, 0, 1, 0, 0, 0]], ['double', None]], ['control [[1, 0, 1, 0, 0, 1, 0, 1]]', [[1, 0, 1, 0, 0, 1, 0, 1]], ['clean', [0, 1, 0, 1]]], ['control [[1, 0, 1, 1, 0, 1, 1, 1]]', [[1, 0, 1, 1, 0, 1, 1, 1]], ['double', None]]], [['regression [[0, 1, 0, 0, 0, 1, 0, 1]]', [[0, 1, 0, 0, 0, 1, 0, 1]], ['corrected', [1, 1, 0, 1]]], ['regression [[0, 0, 0, 1, 0, 1, 1, 0]]', [[0, 0, 0, 1, 0, 1, 1, 0]], ['corrected', [1, 1, 1, 0]]], ['partial-repair [[1, 1, 1, 0, 1, 1, 1, 1]]', [[1, 1, 1, 0, 1, 1, 1, 1]], ['corrected', [1, 1, 1, 1]]], ['partial-repair [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 1, 1, 0, 0, 1, 1, 0]]', [[0, 1, 1, 0, 0, 1, 1, 0]], ['clean', [0, 1, 1, 0]]], ['control [[0, 0, 1, 0, 0, 0, 1, 0]]', [[0, 0, 1, 0, 0, 0, 1, 0]], ['double', None]], ['control [[0, 0, 0, 0, 1, 1, 1, 1]]', [[0, 0, 0, 0, 1, 1, 1, 1]], ['clean', [0, 1, 1, 1]]], ['control [[0, 0, 0, 0, 0, 1, 1, 0]]', [[0, 0, 0, 0, 0, 1, 1, 0]], ['double', None]]], [['regression [[1, 0, 0, 0, 0, 0, 0, 0]]', [[1, 0, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['regression [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['partial-repair [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['partial-repair [[1, 0, 1, 0, 0, 1, 1, 1]]', [[1, 0, 1, 0, 0, 1, 1, 1]], ['corrected', [0, 1, 0, 1]]], ['control [[1, 1, 0, 1, 0, 1, 0, 0]]', [[1, 1, 0, 1, 0, 1, 0, 0]], ['double', None]], ['control [[1, 0, 0, 1, 1, 0, 0, 1]]', [[1, 0, 0, 1, 1, 0, 0, 1]], ['clean', [1, 0, 0, 1]]], ['control [[1, 1, 0, 0, 1, 0, 0, 1]]', [[1, 1, 0, 0, 1, 0, 0, 1]], ['double', None]], ['control [[0, 1, 0, 1, 1, 0, 1, 0]]', [[0, 1, 0, 1, 1, 0, 1, 0]], ['clean', [1, 0, 1, 0]]]]]
for label, args, expected in fixtures[N - 1]:
    check(label, solve(*args), expected)
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
regression [[0, 1, 1, 0, 1, 1, 0, 1]]['corrected', [0, 1, 0, 1]]['corrected', [0, 0, 0, 1]]Failed
regression [[1, 0, 1, 0, 1, 1, 1, 0]]['corrected', [0, 1, 1, 0]]['corrected', [0, 0, 1, 0]]Failed
control [[0, 0, 0, 0, 0, 0, 0, 0]]['clean', [0, 0, 0, 0]]['clean', [0, 0, 0, 0]]Passed
control [[0, 1, 0, 0, 0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]Passed
control [[0, 0, 0, 0, 0, 0, 1, 1]]['double', None]['double', None]Passed
control [[0, 1, 1, 0, 1, 0, 0, 1]]['clean', [0, 0, 0, 1]]['clean', [0, 0, 0, 1]]Passed
control [[0, 1, 0, 1, 1, 0, 0, 1]]['double', None]['double', None]Passed
control [[1, 0, 1, 0, 1, 0, 1, 0]]['clean', [0, 0, 1, 0]]['clean', [0, 0, 1, 0]]Passed

SHA-256 / f8f5e759686191e7824587b0a7c3b9fe53aa28fac10848543bb935f98e7c2e13

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(r):
    if len(r) != 8 or any(b not in (0, 1) for b in r):
        return None
    s = 0
    for pos in range(1, 8):
        if r[pos]:
            s ^= pos
    p = sum(r) % 2
    c = list(r)
    if s == 0 and p == 0:
        status = 'clean'
    elif p == 1:
        status = 'corrected'
        c[max(s - 1, 0)] ^= 1
    else:
        return ['double', None]
    return [status, [c[3], c[5], c[6], c[7]]]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression [[0, 1, 1, 0, 1, 1, 0, 1]]', [[0, 1, 1, 0, 1, 1, 0, 1]], ['corrected', [0, 0, 0, 1]]], ['regression [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['control [[0, 0, 0, 0, 0, 0, 0, 0]]', [[0, 0, 0, 0, 0, 0, 0, 0]], ['clean', [0, 0, 0, 0]]], ['control [[0, 1, 0, 0, 0, 0, 0, 0]]', [[0, 1, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 0, 0, 0, 0, 0, 1, 1]]', [[0, 0, 0, 0, 0, 0, 1, 1]], ['double', None]], ['control [[0, 1, 1, 0, 1, 0, 0, 1]]', [[0, 1, 1, 0, 1, 0, 0, 1]], ['clean', [0, 0, 0, 1]]], ['control [[0, 1, 0, 1, 1, 0, 0, 1]]', [[0, 1, 0, 1, 1, 0, 0, 1]], ['double', None]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]]], [['regression [[0, 1, 1, 0, 0, 0, 1, 0]]', [[0, 1, 1, 0, 0, 0, 1, 0]], ['corrected', [0, 1, 1, 0]]], ['regression [[0, 0, 0, 0, 1, 1, 1, 0]]', [[0, 0, 0, 0, 1, 1, 1, 0]], ['corrected', [0, 1, 1, 1]]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]], ['control [[1, 0, 0, 1, 1, 0, 1, 0]]', [[1, 0, 0, 1, 1, 0, 1, 0]], ['double', None]], ['control [[1, 1, 0, 0, 0, 0, 1, 1]]', [[1, 1, 0, 0, 0, 0, 1, 1]], ['clean', [0, 0, 1, 1]]], ['control [[1, 1, 1, 0, 0, 0, 1, 1]]', [[1, 1, 1, 0, 0, 0, 1, 1]], ['corrected', [0, 0, 1, 1]]], ['control [[1, 1, 0, 1, 0, 0, 0, 1]]', [[1, 1, 0, 1, 0, 0, 0, 1]], ['double', None]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]]], [['regression [[1, 0, 0, 1, 1, 0, 0, 0]]', [[1, 0, 0, 1, 1, 0, 0, 0]], ['corrected', [1, 0, 0, 1]]], ['regression [[0, 1, 0, 0, 1, 0, 1, 0]]', [[0, 1, 0, 0, 1, 0, 1, 0]], ['corrected', [1, 0, 1, 0]]], ['partial-repair [[0, 0, 1, 1, 0, 1, 1, 1]]', [[0, 0, 1, 1, 0, 1, 1, 1]], ['corrected', [1, 0, 1, 1]]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]], ['control [[1, 1, 1, 0, 1, 1, 0, 0]]', [[1, 1, 1, 0, 1, 1, 0, 0]], ['corrected', [0, 1, 0, 0]]], ['control [[1, 0, 0, 0, 1, 0, 0, 0]]', [[1, 0, 0, 0, 1, 0, 0, 0]], ['double', None]], ['control [[1, 0, 1, 0, 0, 1, 0, 1]]', [[1, 0, 1, 0, 0, 1, 0, 1]], ['clean', [0, 1, 0, 1]]], ['control [[1, 0, 1, 1, 0, 1, 1, 1]]', [[1, 0, 1, 1, 0, 1, 1, 1]], ['double', None]]], [['regression [[0, 1, 0, 0, 0, 1, 0, 1]]', [[0, 1, 0, 0, 0, 1, 0, 1]], ['corrected', [1, 1, 0, 1]]], ['regression [[0, 0, 0, 1, 0, 1, 1, 0]]', [[0, 0, 0, 1, 0, 1, 1, 0]], ['corrected', [1, 1, 1, 0]]], ['partial-repair [[1, 1, 1, 0, 1, 1, 1, 1]]', [[1, 1, 1, 0, 1, 1, 1, 1]], ['corrected', [1, 1, 1, 1]]], ['partial-repair [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 1, 1, 0, 0, 1, 1, 0]]', [[0, 1, 1, 0, 0, 1, 1, 0]], ['clean', [0, 1, 1, 0]]], ['control [[0, 0, 1, 0, 0, 0, 1, 0]]', [[0, 0, 1, 0, 0, 0, 1, 0]], ['double', None]], ['control [[0, 0, 0, 0, 1, 1, 1, 1]]', [[0, 0, 0, 0, 1, 1, 1, 1]], ['clean', [0, 1, 1, 1]]], ['control [[0, 0, 0, 0, 0, 1, 1, 0]]', [[0, 0, 0, 0, 0, 1, 1, 0]], ['double', None]]], [['regression [[1, 0, 0, 0, 0, 0, 0, 0]]', [[1, 0, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['regression [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['partial-repair [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['partial-repair [[1, 0, 1, 0, 0, 1, 1, 1]]', [[1, 0, 1, 0, 0, 1, 1, 1]], ['corrected', [0, 1, 0, 1]]], ['control [[1, 1, 0, 1, 0, 1, 0, 0]]', [[1, 1, 0, 1, 0, 1, 0, 0]], ['double', None]], ['control [[1, 0, 0, 1, 1, 0, 0, 1]]', [[1, 0, 0, 1, 1, 0, 0, 1]], ['clean', [1, 0, 0, 1]]], ['control [[1, 1, 0, 0, 1, 0, 0, 1]]', [[1, 1, 0, 0, 1, 0, 0, 1]], ['double', None]], ['control [[0, 1, 0, 1, 1, 0, 1, 0]]', [[0, 1, 0, 1, 1, 0, 1, 0]], ['clean', [1, 0, 1, 0]]]]]
for label, args, expected in fixtures[N - 1]:
    check(label, solve(*args), expected)
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
regression [[0, 1, 1, 0, 1, 1, 0, 1]]['corrected', [0, 1, 0, 1]]['corrected', [0, 0, 0, 1]]Failed
regression [[1, 0, 1, 0, 1, 1, 1, 0]]['corrected', [0, 1, 1, 0]]['corrected', [0, 0, 1, 0]]Failed
control [[0, 0, 0, 0, 0, 0, 0, 0]]['clean', [0, 0, 0, 0]]['clean', [0, 0, 0, 0]]Passed
control [[0, 1, 0, 0, 0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]Passed
control [[0, 0, 0, 0, 0, 0, 1, 1]]['double', None]['double', None]Passed
control [[0, 1, 1, 0, 1, 0, 0, 1]]['clean', [0, 0, 0, 1]]['clean', [0, 0, 0, 1]]Passed
control [[0, 1, 0, 1, 1, 0, 0, 1]]['double', None]['double', None]Passed
control [[1, 0, 1, 0, 1, 0, 1, 0]]['clean', [0, 0, 1, 0]]['clean', [0, 0, 1, 0]]Passed

SHA-256 / baefb946d5b4413bd520500cc2550adfd3ed3bbd9a9ea91d0c8c91373a3c97a3

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(r):
    if len(r) != 8 or any(b not in (0, 1) for b in r):
        return None
    s = 0
    for pos in range(1, 8):
        if r[pos]:
            s ^= pos
    p = sum(r) % 2
    c = list(r)
    if s == 0 and p == 0:
        status = 'clean'
    elif p == 1:
        status = 'corrected'
        c[s] ^= 1
    else:
        return ['double', None]
    return [status, [c[3], c[5], c[6], c[7]]]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression [[0, 1, 1, 0, 1, 1, 0, 1]]', [[0, 1, 1, 0, 1, 1, 0, 1]], ['corrected', [0, 0, 0, 1]]], ['regression [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['control [[0, 0, 0, 0, 0, 0, 0, 0]]', [[0, 0, 0, 0, 0, 0, 0, 0]], ['clean', [0, 0, 0, 0]]], ['control [[0, 1, 0, 0, 0, 0, 0, 0]]', [[0, 1, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 0, 0, 0, 0, 0, 1, 1]]', [[0, 0, 0, 0, 0, 0, 1, 1]], ['double', None]], ['control [[0, 1, 1, 0, 1, 0, 0, 1]]', [[0, 1, 1, 0, 1, 0, 0, 1]], ['clean', [0, 0, 0, 1]]], ['control [[0, 1, 0, 1, 1, 0, 0, 1]]', [[0, 1, 0, 1, 1, 0, 0, 1]], ['double', None]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]]], [['regression [[0, 1, 1, 0, 0, 0, 1, 0]]', [[0, 1, 1, 0, 0, 0, 1, 0]], ['corrected', [0, 1, 1, 0]]], ['regression [[0, 0, 0, 0, 1, 1, 1, 0]]', [[0, 0, 0, 0, 1, 1, 1, 0]], ['corrected', [0, 1, 1, 1]]], ['control [[1, 0, 1, 0, 1, 0, 1, 0]]', [[1, 0, 1, 0, 1, 0, 1, 0]], ['clean', [0, 0, 1, 0]]], ['control [[1, 0, 0, 1, 1, 0, 1, 0]]', [[1, 0, 0, 1, 1, 0, 1, 0]], ['double', None]], ['control [[1, 1, 0, 0, 0, 0, 1, 1]]', [[1, 1, 0, 0, 0, 0, 1, 1]], ['clean', [0, 0, 1, 1]]], ['control [[1, 1, 1, 0, 0, 0, 1, 1]]', [[1, 1, 1, 0, 0, 0, 1, 1]], ['corrected', [0, 0, 1, 1]]], ['control [[1, 1, 0, 1, 0, 0, 0, 1]]', [[1, 1, 0, 1, 0, 0, 0, 1]], ['double', None]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]]], [['regression [[1, 0, 0, 1, 1, 0, 0, 0]]', [[1, 0, 0, 1, 1, 0, 0, 0]], ['corrected', [1, 0, 0, 1]]], ['regression [[0, 1, 0, 0, 1, 0, 1, 0]]', [[0, 1, 0, 0, 1, 0, 1, 0]], ['corrected', [1, 0, 1, 0]]], ['partial-repair [[0, 0, 1, 1, 0, 1, 1, 1]]', [[0, 0, 1, 1, 0, 1, 1, 1]], ['corrected', [1, 0, 1, 1]]], ['control [[1, 1, 0, 0, 1, 1, 0, 0]]', [[1, 1, 0, 0, 1, 1, 0, 0]], ['clean', [0, 1, 0, 0]]], ['control [[1, 1, 1, 0, 1, 1, 0, 0]]', [[1, 1, 1, 0, 1, 1, 0, 0]], ['corrected', [0, 1, 0, 0]]], ['control [[1, 0, 0, 0, 1, 0, 0, 0]]', [[1, 0, 0, 0, 1, 0, 0, 0]], ['double', None]], ['control [[1, 0, 1, 0, 0, 1, 0, 1]]', [[1, 0, 1, 0, 0, 1, 0, 1]], ['clean', [0, 1, 0, 1]]], ['control [[1, 0, 1, 1, 0, 1, 1, 1]]', [[1, 0, 1, 1, 0, 1, 1, 1]], ['double', None]]], [['regression [[0, 1, 0, 0, 0, 1, 0, 1]]', [[0, 1, 0, 0, 0, 1, 0, 1]], ['corrected', [1, 1, 0, 1]]], ['regression [[0, 0, 0, 1, 0, 1, 1, 0]]', [[0, 0, 0, 1, 0, 1, 1, 0]], ['corrected', [1, 1, 1, 0]]], ['partial-repair [[1, 1, 1, 0, 1, 1, 1, 1]]', [[1, 1, 1, 0, 1, 1, 1, 1]], ['corrected', [1, 1, 1, 1]]], ['partial-repair [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['control [[0, 1, 1, 0, 0, 1, 1, 0]]', [[0, 1, 1, 0, 0, 1, 1, 0]], ['clean', [0, 1, 1, 0]]], ['control [[0, 0, 1, 0, 0, 0, 1, 0]]', [[0, 0, 1, 0, 0, 0, 1, 0]], ['double', None]], ['control [[0, 0, 0, 0, 1, 1, 1, 1]]', [[0, 0, 0, 0, 1, 1, 1, 1]], ['clean', [0, 1, 1, 1]]], ['control [[0, 0, 0, 0, 0, 1, 1, 0]]', [[0, 0, 0, 0, 0, 1, 1, 0]], ['double', None]]], [['regression [[1, 0, 0, 0, 0, 0, 0, 0]]', [[1, 0, 0, 0, 0, 0, 0, 0]], ['corrected', [0, 0, 0, 0]]], ['regression [[0, 0, 0, 0, 0, 0, 0, 1]]', [[0, 0, 0, 0, 0, 0, 0, 1]], ['corrected', [0, 0, 0, 0]]], ['partial-repair [[1, 0, 1, 0, 1, 1, 1, 0]]', [[1, 0, 1, 0, 1, 1, 1, 0]], ['corrected', [0, 0, 1, 0]]], ['partial-repair [[1, 0, 1, 0, 0, 1, 1, 1]]', [[1, 0, 1, 0, 0, 1, 1, 1]], ['corrected', [0, 1, 0, 1]]], ['control [[1, 1, 0, 1, 0, 1, 0, 0]]', [[1, 1, 0, 1, 0, 1, 0, 0]], ['double', None]], ['control [[1, 0, 0, 1, 1, 0, 0, 1]]', [[1, 0, 0, 1, 1, 0, 0, 1]], ['clean', [1, 0, 0, 1]]], ['control [[1, 1, 0, 0, 1, 0, 0, 1]]', [[1, 1, 0, 0, 1, 0, 0, 1]], ['double', None]], ['control [[0, 1, 0, 1, 1, 0, 1, 0]]', [[0, 1, 0, 1, 1, 0, 1, 0]], ['clean', [1, 0, 1, 0]]]]]
for label, args, expected in fixtures[N - 1]:
    check(label, solve(*args), expected)
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
regression [[0, 1, 1, 0, 1, 1, 0, 1]]['corrected', [0, 0, 0, 1]]['corrected', [0, 0, 0, 1]]Passed
regression [[1, 0, 1, 0, 1, 1, 1, 0]]['corrected', [0, 0, 1, 0]]['corrected', [0, 0, 1, 0]]Passed
control [[0, 0, 0, 0, 0, 0, 0, 0]]['clean', [0, 0, 0, 0]]['clean', [0, 0, 0, 0]]Passed
control [[0, 1, 0, 0, 0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]['corrected', [0, 0, 0, 0]]Passed
control [[0, 0, 0, 0, 0, 0, 1, 1]]['double', None]['double', None]Passed
control [[0, 1, 1, 0, 1, 0, 0, 1]]['clean', [0, 0, 0, 1]]['clean', [0, 0, 0, 1]]Passed
control [[0, 1, 0, 1, 1, 0, 0, 1]]['double', None]['double', None]Passed
control [[1, 0, 1, 0, 1, 0, 1, 0]]['clean', [0, 0, 1, 0]]['clean', [0, 0, 1, 0]]Passed

SHA-256 / 545cf636fa4568e54f83d4a060956968722c3abd7cb3d6520198de32435d33e0

Verification & scope

A deterministic, bounded teaching model of the named code under the stated contract; not a production codec. 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 2026-09-29T14:48:33.569145+00:00.

Case digest / 10b99e2ba093870e40a7e17062af6f764d7601d64383c3a1d2b4c1f213dff465