FA-79696 / Barcode symbology encoding / Open access

QR terminator overflows a nearly full symbol · case 01

Payloads that fill all but a few bits get an extra codeword and the symbol is rejected as too long.

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

ROOT CAUSE

The four-bit terminator is appended even when fewer than four bits remain.

VERIFIED REPAIR

Truncate the terminator to the remaining capacity.

Unsuccessful approach: Skipping the terminator for byte-aligned data starts padding immediately after the data.

Case contract

Finish a QR data bit stream for a symbol with `capacity` data codewords: data longer than capacity*8 bits returns None; append a terminator of up to four 0 bits (truncated if capacity is reached), pad with 0 bits to a byte boundary, split into codewords, then append pad codewords alternating 0xEC, 0x11 starting with 0xEC until the capacity is filled.

Why this case matters

Retail, logistics, pharmacy and document workflows depend on encoders that produce exactly the module pattern, code-set switches, separators and quiet zones scanners expect; one misplaced module or separator makes a label unreadable or, worse, scan as different data.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(bits, capacity):
    cap = capacity * 8
    if len(bits) > cap:
        return None
    bits += '0' * 4
    bits += '0' * (-len(bits) % 8)
    words = [int(bits[i:i + 8], 2) for i in range(0, len(bits), 8)]
    pads = [0xEC, 0x11]
    k = 0
    while len(words) < capacity:
        words.append(pads[k % 2])
        k += 1
    return words
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[('11110', 1), [240]], [('011111010101101111101000', 5), [125, 91, 232, 0, 236]], [('101011111101111010101001010011000', 4), None], [('001101110111100101001100111101010', 4), None], [('11000111110010110000011101', 7), [199, 203, 7, 64, 236, 17, 236]], [('100011010101010010101011001011100010011001011001110101101', 7), None], [('11100101110010101101110100001101011110011', 5), None], [('10111110000100110101101101110110', 4), [190, 19, 91, 118]]], [[('0110001100001', 2), [99, 8]], [('1010101101000100', 3), [171, 68, 0]], [('10110001011011111', 2), None], [('010111100111111111101011010111010101', 6), [94, 127, 235, 93, 80, 236]], [('00101010101111110010011110110010011100110', 5), None], [('1110111100000001110000101', 3), None], [('10110001001101011', 2), None], [('11001010100001101100111010101111110110110010001101011100', 7), [202, 134, 206, 175, 219, 35, 92]]], [[('10110101', 1), [181]], [('0110000101010010', 7), [97, 82, 0, 236, 17, 236, 17]], [('11010010000000100000001', 4), [210, 2, 2, 0]], [('10100010001101111', 2), None], [('111010111110010110000100101101100011001010010011111010111', 7), None], [('1100011111010101100100001111010111100110101001110', 6), None], [('110011111', 1), None], [('1110100000110001011011010010010', 4), [232, 49, 109, 36]]], [[('01110011101100110010100111000111100111011111110101101110', 7), [115, 179, 41, 199, 157, 253, 110]], [('0111001011100011', 5), [114, 227, 0, 236, 17]], [('0001101010100101110100100000001001110111000110110', 6), None], [('10001101000010011', 2), None], [('1010100000100110011011001000111101000001101100001', 6), None], [('0000101000111100101001100', 3), None], [('10110000110100000110100001110011111101000', 5), None], [('00011', 1), [24]]], [[('100100000001111010001', 3), [144, 30, 136]], [('1010010001000111', 3), [164, 71, 0]], [('0110100001000100000', 7), [104, 68, 0, 236, 17, 236, 17]], [('000101100', 1), None], [('100010101011001101000110110111110', 4), None], [('0100011110111010010001', 5), [71, 186, 68, 0, 236]], [('1011000001110101001101010100', 6), [176, 117, 53, 64, 236, 17]], [('1001000010101110001111000110111010001110', 5), [144, 174, 60, 110, 142]]]]
labels = ["regression: terminator truncation at capacity", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("%s %d" % (labels[i % len(labels)], i), 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 fixture	Actual	Expected	Outcome
regression: terminator truncation at capacity 0	`[240, 0]`	`[240]`	Failed
repair trap 1	`[125, 91, 232, 0, 236]`	`[125, 91, 232, 0, 236]`	Passed
combined fault 2	`None`	`None`	Passed
control 3	`None`	`None`	Passed
control 4	`[199, 203, 7, 64, 236, 17, 236]`	`[199, 203, 7, 64, 236, 17, 236]`	Passed
boundary 5	`None`	`None`	Passed
boundary 6	`None`	`None`	Passed
control 7	`[190, 19, 91, 118, 0]`	`[190, 19, 91, 118]`	Failed

SHA-256 / 193e5b83ce12479a3324006881781a8d221a9e18d6585a2f03d7e020d4bf9857

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(bits, capacity):
    cap = capacity * 8
    if len(bits) > cap:
        return None
    bits += '0' * min(4, cap - len(bits)) if len(bits) % 8 else ''
    bits += '0' * (-len(bits) % 8)
    words = [int(bits[i:i + 8], 2) for i in range(0, len(bits), 8)]
    pads = [0xEC, 0x11]
    k = 0
    while len(words) < capacity:
        words.append(pads[k % 2])
        k += 1
    return words
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[('11110', 1), [240]], [('011111010101101111101000', 5), [125, 91, 232, 0, 236]], [('101011111101111010101001010011000', 4), None], [('001101110111100101001100111101010', 4), None], [('11000111110010110000011101', 7), [199, 203, 7, 64, 236, 17, 236]], [('100011010101010010101011001011100010011001011001110101101', 7), None], [('11100101110010101101110100001101011110011', 5), None], [('10111110000100110101101101110110', 4), [190, 19, 91, 118]]], [[('0110001100001', 2), [99, 8]], [('1010101101000100', 3), [171, 68, 0]], [('10110001011011111', 2), None], [('010111100111111111101011010111010101', 6), [94, 127, 235, 93, 80, 236]], [('00101010101111110010011110110010011100110', 5), None], [('1110111100000001110000101', 3), None], [('10110001001101011', 2), None], [('11001010100001101100111010101111110110110010001101011100', 7), [202, 134, 206, 175, 219, 35, 92]]], [[('10110101', 1), [181]], [('0110000101010010', 7), [97, 82, 0, 236, 17, 236, 17]], [('11010010000000100000001', 4), [210, 2, 2, 0]], [('10100010001101111', 2), None], [('111010111110010110000100101101100011001010010011111010111', 7), None], [('1100011111010101100100001111010111100110101001110', 6), None], [('110011111', 1), None], [('1110100000110001011011010010010', 4), [232, 49, 109, 36]]], [[('01110011101100110010100111000111100111011111110101101110', 7), [115, 179, 41, 199, 157, 253, 110]], [('0111001011100011', 5), [114, 227, 0, 236, 17]], [('0001101010100101110100100000001001110111000110110', 6), None], [('10001101000010011', 2), None], [('1010100000100110011011001000111101000001101100001', 6), None], [('0000101000111100101001100', 3), None], [('10110000110100000110100001110011111101000', 5), None], [('00011', 1), [24]]], [[('100100000001111010001', 3), [144, 30, 136]], [('1010010001000111', 3), [164, 71, 0]], [('0110100001000100000', 7), [104, 68, 0, 236, 17, 236, 17]], [('000101100', 1), None], [('100010101011001101000110110111110', 4), None], [('0100011110111010010001', 5), [71, 186, 68, 0, 236]], [('1011000001110101001101010100', 6), [176, 117, 53, 64, 236, 17]], [('1001000010101110001111000110111010001110', 5), [144, 174, 60, 110, 142]]]]
labels = ["regression: terminator truncation at capacity", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("%s %d" % (labels[i % len(labels)], i), 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 fixture	Actual	Expected	Outcome
regression: terminator truncation at capacity 0	`[240]`	`[240]`	Passed
repair trap 1	`[125, 91, 232, 236, 17]`	`[125, 91, 232, 0, 236]`	Failed
combined fault 2	`None`	`None`	Passed
control 3	`None`	`None`	Passed
control 4	`[199, 203, 7, 64, 236, 17, 236]`	`[199, 203, 7, 64, 236, 17, 236]`	Passed
boundary 5	`None`	`None`	Passed
boundary 6	`None`	`None`	Passed
control 7	`[190, 19, 91, 118]`	`[190, 19, 91, 118]`	Passed

SHA-256 / 87a7ea1bab55194cd687d7614f8090fa868c8877b814a69726048c6595e92fa4

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(bits, capacity):
    cap = capacity * 8
    if len(bits) > cap:
        return None
    bits += '0' * min(4, cap - len(bits))
    bits += '0' * (-len(bits) % 8)
    words = [int(bits[i:i + 8], 2) for i in range(0, len(bits), 8)]
    pads = [0xEC, 0x11]
    k = 0
    while len(words) < capacity:
        words.append(pads[k % 2])
        k += 1
    return words
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[('11110', 1), [240]], [('011111010101101111101000', 5), [125, 91, 232, 0, 236]], [('101011111101111010101001010011000', 4), None], [('001101110111100101001100111101010', 4), None], [('11000111110010110000011101', 7), [199, 203, 7, 64, 236, 17, 236]], [('100011010101010010101011001011100010011001011001110101101', 7), None], [('11100101110010101101110100001101011110011', 5), None], [('10111110000100110101101101110110', 4), [190, 19, 91, 118]]], [[('0110001100001', 2), [99, 8]], [('1010101101000100', 3), [171, 68, 0]], [('10110001011011111', 2), None], [('010111100111111111101011010111010101', 6), [94, 127, 235, 93, 80, 236]], [('00101010101111110010011110110010011100110', 5), None], [('1110111100000001110000101', 3), None], [('10110001001101011', 2), None], [('11001010100001101100111010101111110110110010001101011100', 7), [202, 134, 206, 175, 219, 35, 92]]], [[('10110101', 1), [181]], [('0110000101010010', 7), [97, 82, 0, 236, 17, 236, 17]], [('11010010000000100000001', 4), [210, 2, 2, 0]], [('10100010001101111', 2), None], [('111010111110010110000100101101100011001010010011111010111', 7), None], [('1100011111010101100100001111010111100110101001110', 6), None], [('110011111', 1), None], [('1110100000110001011011010010010', 4), [232, 49, 109, 36]]], [[('01110011101100110010100111000111100111011111110101101110', 7), [115, 179, 41, 199, 157, 253, 110]], [('0111001011100011', 5), [114, 227, 0, 236, 17]], [('0001101010100101110100100000001001110111000110110', 6), None], [('10001101000010011', 2), None], [('1010100000100110011011001000111101000001101100001', 6), None], [('0000101000111100101001100', 3), None], [('10110000110100000110100001110011111101000', 5), None], [('00011', 1), [24]]], [[('100100000001111010001', 3), [144, 30, 136]], [('1010010001000111', 3), [164, 71, 0]], [('0110100001000100000', 7), [104, 68, 0, 236, 17, 236, 17]], [('000101100', 1), None], [('100010101011001101000110110111110', 4), None], [('0100011110111010010001', 5), [71, 186, 68, 0, 236]], [('1011000001110101001101010100', 6), [176, 117, 53, 64, 236, 17]], [('1001000010101110001111000110111010001110', 5), [144, 174, 60, 110, 142]]]]
labels = ["regression: terminator truncation at capacity", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check("%s %d" % (labels[i % len(labels)], i), 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 fixture	Actual	Expected	Outcome
regression: terminator truncation at capacity 0	`[240]`	`[240]`	Passed
repair trap 1	`[125, 91, 232, 0, 236]`	`[125, 91, 232, 0, 236]`	Passed
combined fault 2	`None`	`None`	Passed
control 3	`None`	`None`	Passed
control 4	`[199, 203, 7, 64, 236, 17, 236]`	`[199, 203, 7, 64, 236, 17, 236]`	Passed
boundary 5	`None`	`None`	Passed
boundary 6	`None`	`None`	Passed
control 7	`[190, 19, 91, 118]`	`[190, 19, 91, 118]`	Passed

SHA-256 / f92b400351c1b2dde877d9b16f48a6ad1d0e578ec9f7b2782553d5c6062d826b

Verification & scope

A deterministic bounded teaching model with a stipulated contract; it makes no claim of conformance to any published specification. 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 2026-09-29T14:49:46.946895+00:00.

Case digest / 5a17d27b5f4d041892ceb1a86ff8083453fb368ae63d6327d67eccaf9a062641