FAILURE MAP
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FA-72721 / Check-digit algorithms / Open access

Container weights start at two · case 01

Every container number fails its check.

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

ROOT CAUSE

Weights are 2^(i+1), doubling every term.

THE FAILURE

Weights are 2^(i+1), doubling every term.

Unsuccessful approach: Reversing the exponent assigns 2^9 to the owner code instead of the serial number.

Case contract

Shipping container identification check digit: three uppercase owner letters, category U, J or Z, six serial digits and a check digit (else "malformed"). Letter values start at A=10 and skip every multiple of 11 (so B=12, L=23, V=34, Z=38). Position i (0-based) has weight 2^i; the check digit is (sum mod 11) mod 10. Return [check, match].

Why this case matters

Terminal gate systems validate container numbers read by OCR cameras before booking moves.

1 / The failure

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

N = 1
observations = []
def solve(s):
    if len(s) != 11 or not s.isascii() or not s[:3].isalpha() or not s[:3].isupper():
        return 'malformed'
    if s[3] not in 'UJZ' or not s[4:].isdigit():
        return 'malformed'
    vals = {}
    v = 10
    for ch in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ':
        if v % 11 == 0:
            v += 1
        vals[ch] = v
        v += 1
    total = 0
    for i, ch in enumerate(s[:10]):
        total += (vals[ch] if ch.isalpha() else int(ch)) * 2 ** (i + 1)
    check = total % 11 % 10
    return [check, check == int(s[10])]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression ["HRNU7843702"]', ['HRNU7843702'], [9, False]], ['regression ["BYYJ6917585"]', ['BYYJ6917585'], [8, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed'], ['control ["YQEU5793145"]', ['YQEU5793145'], [6, False]]], [['regression ["MUHJ6260452"]', ['MUHJ6260452'], [4, False]], ['regression ["GEDJ3497886"]', ['GEDJ3497886'], [3, False]], ['partial-repair ["YQEU5793145"]', ['YQEU5793145'], [6, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["CTZU8384457"]', ['CTZU8384457'], [2, False]], ['regression ["CYVU1050697"]', ['CYVU1050697'], [7, True]], ['partial-repair ["FLAU0380833"]', ['FLAU0380833'], [7, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["OQHU9278051"]', ['OQHU9278051'], [8, False]], ['regression ["TRVJ4468592"]', ['TRVJ4468592'], [8, False]], ['partial-repair ["LGSU0173454"]', ['LGSU0173454'], [8, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["RGOU0215685"]', ['RGOU0215685'], [3, False]], ['regression ["LBRU3332332"]', ['LBRU3332332'], [4, False]], ['partial-repair ["TSAZ4635083"]', ['TSAZ4635083'], [9, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']]]
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 ["HRNU7843702"][7, False][9, False]Failed
regression ["BYYJ6917585"][5, True][8, False]Failed
control ["VQAJ3159690"][0, True][0, True]Passed
control ["CSQU305438"]malformedmalformedPassed
control ["CSQX3054383"]malformedmalformedPassed
control ["csqu3054383"]malformedmalformedPassed
control ["C1QU3054383"]malformedmalformedPassed
control ["YQEU5793145"][1, False][6, False]Failed

SHA-256 / 4f4d248c5f4f591e62883b4d937ba204a123b6167d753521142fd85bc709e5a7

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(s):
    if len(s) != 11 or not s.isascii() or not s[:3].isalpha() or not s[:3].isupper():
        return 'malformed'
    if s[3] not in 'UJZ' or not s[4:].isdigit():
        return 'malformed'
    vals = {}
    v = 10
    for ch in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ':
        if v % 11 == 0:
            v += 1
        vals[ch] = v
        v += 1
    total = 0
    for i, ch in enumerate(s[:10]):
        total += (vals[ch] if ch.isalpha() else int(ch)) * 2 ** (9 - i)
    check = total % 11 % 10
    return [check, check == int(s[10])]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[['regression ["HRNU7843702"]', ['HRNU7843702'], [9, False]], ['regression ["BYYJ6917585"]', ['BYYJ6917585'], [8, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed'], ['control ["YQEU5793145"]', ['YQEU5793145'], [6, False]]], [['regression ["MUHJ6260452"]', ['MUHJ6260452'], [4, False]], ['regression ["GEDJ3497886"]', ['GEDJ3497886'], [3, False]], ['partial-repair ["YQEU5793145"]', ['YQEU5793145'], [6, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["CTZU8384457"]', ['CTZU8384457'], [2, False]], ['regression ["CYVU1050697"]', ['CYVU1050697'], [7, True]], ['partial-repair ["FLAU0380833"]', ['FLAU0380833'], [7, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["OQHU9278051"]', ['OQHU9278051'], [8, False]], ['regression ["TRVJ4468592"]', ['TRVJ4468592'], [8, False]], ['partial-repair ["LGSU0173454"]', ['LGSU0173454'], [8, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']], [['regression ["RGOU0215685"]', ['RGOU0215685'], [3, False]], ['regression ["LBRU3332332"]', ['LBRU3332332'], [4, False]], ['partial-repair ["TSAZ4635083"]', ['TSAZ4635083'], [9, False]], ['control ["VQAJ3159690"]', ['VQAJ3159690'], [0, True]], ['control ["CSQU305438"]', ['CSQU305438'], 'malformed'], ['control ["CSQX3054383"]', ['CSQX3054383'], 'malformed'], ['control ["csqu3054383"]', ['csqu3054383'], 'malformed'], ['control ["C1QU3054383"]', ['C1QU3054383'], 'malformed']]]
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 ["HRNU7843702"][1, False][9, False]Failed
regression ["BYYJ6917585"][0, False][8, False]Failed
control ["VQAJ3159690"][0, True][0, True]Passed
control ["CSQU305438"]malformedmalformedPassed
control ["CSQX3054383"]malformedmalformedPassed
control ["csqu3054383"]malformedmalformedPassed
control ["C1QU3054383"]malformedmalformedPassed
control ["YQEU5793145"][5, True][6, False]Failed

SHA-256 / 3237f4c01e0c56b12c89332e0a6bedd571cd63cdb6320888ff3602e119c4dbc4

HELD IN THE MEMBER ARCHIVE

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

This mechanism has 8 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

A deterministic, bounded teaching model of the named scheme under the stated contract; not a certified validator. 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 2026-09-29T14:48:41.012753+00:00.

Case digest / e670952e29ff52a649340094ee2330fa061067611f6a8fa1345eb2b376823f8c