FA-79621 / Barcode symbology encoding / Open access
Over-long count field is accepted · case 01
A missing separator after AI 30 merges the next field into the count without an error.
ROOT CAUSE
Variable fields have no maximum length check.
VERIFIED REPAIR
Enforce each AI's own maximum length.
Unsuccessful approach: A global maximum of 20 is wrong for AIs 30, 37 and 400.
Case contract
Parse scanner output of a GS1-128 symbol: it must start with the symbology identifier "]C1"; FNC1 separators arrive as GS (0x1D) and redundant separators are skipped. AIs are recognised by the shortest matching prefix among the predefined fixed-length AIs (00:18, 01/02:14, 11/13/15/17:6, 3103:6) and variable AIs (10/21 max 20, 30/37 max 8, 400 max 30). A fixed field must be complete and contain no GS; a variable field runs to the next GS or the end and must have 1..max characters. Return [[ai, value], ...] or an error.
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(s):
fixed_len = {'00': 18, '01': 14, '02': 14, '11': 6, '13': 6, '15': 6, '17': 6, '3103': 6}
var_max = {'10': 20, '21': 20, '30': 8, '37': 8, '400': 30}
if not s.startswith(']C1'):
return {'error': 'not-gs1'}
i = 3
out = []
while i < len(s):
if s[i] == '\x1d':
i += 1
continue
ai = None
for L in (2, 3, 4):
if s[i:i + L] in fixed_len or s[i:i + L] in var_max:
ai = s[i:i + L]
break
if ai is None:
return {'error': 'unknown-ai', 'at': i}
i += len(ai)
if ai in fixed_len:
n = fixed_len[ai]
val = s[i:i + n]
if len(val) != n or '\x1d' in val:
return {'error': 'short', 'ai': ai}
i += n
else:
j = s.find('\x1d', i)
if j == -1:
j = len(s)
val = s[i:j]
if len(val) < 1:
return {'error': 'length', 'ai': ai}
i = j
out.append([ai, val])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[']C137244121375\x1d21\x1d400XAXCC9C/XXB/1\x1d10/CA', {'error': 'length', 'ai': '37'}], [']C121/9A9-BBAXB9/1CX11A\x1d370168\x1d400XXXXACBAC1A99XX\x1d37958407873', {'error': 'length', 'ai': '37'}], [']C011400783', {'error': 'not-gs1'}], [']C03019\x1d10B9', {'error': 'not-gs1'}], [']C117140648306\x1d0141294680397442\x1d', [['17', '140648'], ['30', '6'], ['01', '41294680397442']]], [']d221B-1BA9-B\x1d219X91//1X9-/1A-C\x1d10BBCB1-9/-/9//-/BC1-A-X\x1d21/ABXAX9C-CC/-\x1d', {'error': 'not-gs1'}], [']C0\x1d3028612956', {'error': 'not-gs1'}], [']C121AC1CXBXC//BB1BCB\x1d310327866137162541688\x1d371', {'error': 'length', 'ai': '37'}]], [[']C12191XXAXB/XX-B91A9-1X1A\x1d10CBAB1-B', {'error': 'length', 'ai': '21'}], [']C13103253004017432790047008137876520261\x1d', {'error': 'length', 'ai': '37'}], [']C13076330559\x1d017350710908563810CX/1/1X//XX//AXCBA-\x1d30467914952', {'error': 'length', 'ai': '30'}], [']C04009\x1d10X-CXA1/X\x1d310311958730', {'error': 'not-gs1'}], [']C10044603095506351280311060380310300579483495402726338', {'error': 'unknown-ai', 'at': 41}], [']d211029205\x1d01139908024073283027281846\x1d10-X9C\x1d', {'error': 'not-gs1'}], [']C1310361473240011XBBC-1-CX1B-\x1d371255\x1d219X9B-C/', [['3103', '614732'], ['400', '11XBBC-1-CX1B-'], ['37', '1255'], ['21', '9X9B-C/']]], [']C137791221293\x1d400A11/1/ACC///CXC1CA/X-\x1d400A-/\x1d37768579', {'error': 'length', 'ai': '37'}]], [[']C121CX1CBA11//99A\x1d018138092042504821XCAA9BX9C91BXBX--B1B-\x1d3103153253', {'error': 'length', 'ai': '21'}], [']C1370404\x1d0169587500743493400C-B1-BAAC9AXXCXAA/B1X\x1d', [['37', '0404'], ['01', '69587500743493'], ['400', 'C-B1-BAAC9AXXCXAA/B1X']]], [']C137364\x1d37951579975\x1d11440863\x1d37038364119\x1d', {'error': 'length', 'ai': '37'}], [']C111362276', [['11', '362276']]], [']C121C-\x1d3103238166', [['21', 'C-'], ['3103', '238166']]], [']C121-/1-X-9B\x1d17420369015026678280984317842704\x1d', [['21', '-/1-X-9B'], ['17', '420369'], ['01', '50266782809843'], ['17', '842704']]], [']C111990558117862\x1d10X-11\x1d0141668383672539', {'error': 'short', 'ai': '11'}], [']C10011511945802272876110ABXB-BA1-B/1X1-BBCXCX1\x1d0143358957494055', {'error': 'length', 'ai': '10'}]], [[']C10153009609031376219XBB-1C-1A9//\x1d1781184810CB9CX-AX--B9ABCCBB9X-C\x1d', {'error': 'length', 'ai': '10'}], [']C121AB/-C9A99/\x1d305405245\x1d00419461779691996360400-1XBCX9CCA9/A-9-1C-11C\x1d', [['21', 'AB/-C9A99/'], ['30', '5405245'], ['00', '419461779691996360'], ['400', '-1XBCX9CCA9/A-9-1C-11C']]], [']C111141665\x1d37247204674\x1d37790824985\x1d00445616335895473473', {'error': 'length', 'ai': '37'}], [']C1211\x1d400/B-\x1d3067920\x1d', [['21', '1'], ['400', '/B-'], ['30', '67920']]], [']C1211CXX-B1B9XXX-/', [['21', '1CXX-B1B9XXX-/']]], [']C1308705431', [['30', '8705431']]], [']C010/ACC1C1C/9\x1d109\x1d00997634519263772689', {'error': 'not-gs1'}], [']C1211\x1d37789365790\x1d30311652\x1d', {'error': 'length', 'ai': '37'}]], [[']C13066\x1d37793432856\x1d3097076472', {'error': 'length', 'ai': '37'}], [']C137505172476\x1d3103210156', {'error': 'length', 'ai': '37'}], [']C137335719723\x1d', {'error': 'length', 'ai': '37'}], [']C037218164131\x1d017878870121363103882288', {'error': 'not-gs1'}], [']C10109147699409412219X9/BACAA-C1/9X19-B\x1d21/\x1d17759960', [['01', '09147699409412'], ['21', '9X9/BACAA-C1/9X19-B'], ['21', '/'], ['17', '759960']]], [']C01109918000653062932206451941', {'error': 'not-gs1'}], [']C017335622\x1d10/A/1X9\x1d1019911-1X/1B1/C-B\x1d400AX/C', {'error': 'not-gs1'}], [']C121-X-BCCC/AB/11/XX-C-B1A\x1d310310809321XX9-CB/X/XAB1XXC', {'error': 'length', 'ai': '21'}]]]
labels = ["regression: variable field maximum", "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: variable field maximum 0 | {'ai': '21', 'error': 'length'} | {'ai': '37', 'error': 'length'} | Failed |
| repair trap 1 | [['21', '/9A9-BBAXB9/1CX11A'], ['37', '0168'], ['400', 'XXXXACBAC1A99XX'], ['37', '958407873']] | {'ai': '37', 'error': 'length'} | Failed |
| combined fault 2 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 3 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 4 | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | Passed |
| boundary 5 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| boundary 6 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 7 | [['21', 'AC1CXBXC//BB1BCB'], ['3103', '278661'], ['37', '162541688'], ['37', '1']] | {'ai': '37', 'error': 'length'} | Failed |
SHA-256 / 360dc706483187442bcdc529484e1051ade994937af2dd6b15af950d8adc9618
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(s):
fixed_len = {'00': 18, '01': 14, '02': 14, '11': 6, '13': 6, '15': 6, '17': 6, '3103': 6}
var_max = {'10': 20, '21': 20, '30': 8, '37': 8, '400': 30}
if not s.startswith(']C1'):
return {'error': 'not-gs1'}
i = 3
out = []
while i < len(s):
if s[i] == '\x1d':
i += 1
continue
ai = None
for L in (2, 3, 4):
if s[i:i + L] in fixed_len or s[i:i + L] in var_max:
ai = s[i:i + L]
break
if ai is None:
return {'error': 'unknown-ai', 'at': i}
i += len(ai)
if ai in fixed_len:
n = fixed_len[ai]
val = s[i:i + n]
if len(val) != n or '\x1d' in val:
return {'error': 'short', 'ai': ai}
i += n
else:
j = s.find('\x1d', i)
if j == -1:
j = len(s)
val = s[i:j]
if not 1 <= len(val) <= 20:
return {'error': 'length', 'ai': ai}
i = j
out.append([ai, val])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[']C137244121375\x1d21\x1d400XAXCC9C/XXB/1\x1d10/CA', {'error': 'length', 'ai': '37'}], [']C121/9A9-BBAXB9/1CX11A\x1d370168\x1d400XXXXACBAC1A99XX\x1d37958407873', {'error': 'length', 'ai': '37'}], [']C011400783', {'error': 'not-gs1'}], [']C03019\x1d10B9', {'error': 'not-gs1'}], [']C117140648306\x1d0141294680397442\x1d', [['17', '140648'], ['30', '6'], ['01', '41294680397442']]], [']d221B-1BA9-B\x1d219X91//1X9-/1A-C\x1d10BBCB1-9/-/9//-/BC1-A-X\x1d21/ABXAX9C-CC/-\x1d', {'error': 'not-gs1'}], [']C0\x1d3028612956', {'error': 'not-gs1'}], [']C121AC1CXBXC//BB1BCB\x1d310327866137162541688\x1d371', {'error': 'length', 'ai': '37'}]], [[']C12191XXAXB/XX-B91A9-1X1A\x1d10CBAB1-B', {'error': 'length', 'ai': '21'}], [']C13103253004017432790047008137876520261\x1d', {'error': 'length', 'ai': '37'}], [']C13076330559\x1d017350710908563810CX/1/1X//XX//AXCBA-\x1d30467914952', {'error': 'length', 'ai': '30'}], [']C04009\x1d10X-CXA1/X\x1d310311958730', {'error': 'not-gs1'}], [']C10044603095506351280311060380310300579483495402726338', {'error': 'unknown-ai', 'at': 41}], [']d211029205\x1d01139908024073283027281846\x1d10-X9C\x1d', {'error': 'not-gs1'}], [']C1310361473240011XBBC-1-CX1B-\x1d371255\x1d219X9B-C/', [['3103', '614732'], ['400', '11XBBC-1-CX1B-'], ['37', '1255'], ['21', '9X9B-C/']]], [']C137791221293\x1d400A11/1/ACC///CXC1CA/X-\x1d400A-/\x1d37768579', {'error': 'length', 'ai': '37'}]], [[']C121CX1CBA11//99A\x1d018138092042504821XCAA9BX9C91BXBX--B1B-\x1d3103153253', {'error': 'length', 'ai': '21'}], [']C1370404\x1d0169587500743493400C-B1-BAAC9AXXCXAA/B1X\x1d', [['37', '0404'], ['01', '69587500743493'], ['400', 'C-B1-BAAC9AXXCXAA/B1X']]], [']C137364\x1d37951579975\x1d11440863\x1d37038364119\x1d', {'error': 'length', 'ai': '37'}], [']C111362276', [['11', '362276']]], [']C121C-\x1d3103238166', [['21', 'C-'], ['3103', '238166']]], [']C121-/1-X-9B\x1d17420369015026678280984317842704\x1d', [['21', '-/1-X-9B'], ['17', '420369'], ['01', '50266782809843'], ['17', '842704']]], [']C111990558117862\x1d10X-11\x1d0141668383672539', {'error': 'short', 'ai': '11'}], [']C10011511945802272876110ABXB-BA1-B/1X1-BBCXCX1\x1d0143358957494055', {'error': 'length', 'ai': '10'}]], [[']C10153009609031376219XBB-1C-1A9//\x1d1781184810CB9CX-AX--B9ABCCBB9X-C\x1d', {'error': 'length', 'ai': '10'}], [']C121AB/-C9A99/\x1d305405245\x1d00419461779691996360400-1XBCX9CCA9/A-9-1C-11C\x1d', [['21', 'AB/-C9A99/'], ['30', '5405245'], ['00', '419461779691996360'], ['400', '-1XBCX9CCA9/A-9-1C-11C']]], [']C111141665\x1d37247204674\x1d37790824985\x1d00445616335895473473', {'error': 'length', 'ai': '37'}], [']C1211\x1d400/B-\x1d3067920\x1d', [['21', '1'], ['400', '/B-'], ['30', '67920']]], [']C1211CXX-B1B9XXX-/', [['21', '1CXX-B1B9XXX-/']]], [']C1308705431', [['30', '8705431']]], [']C010/ACC1C1C/9\x1d109\x1d00997634519263772689', {'error': 'not-gs1'}], [']C1211\x1d37789365790\x1d30311652\x1d', {'error': 'length', 'ai': '37'}]], [[']C13066\x1d37793432856\x1d3097076472', {'error': 'length', 'ai': '37'}], [']C137505172476\x1d3103210156', {'error': 'length', 'ai': '37'}], [']C137335719723\x1d', {'error': 'length', 'ai': '37'}], [']C037218164131\x1d017878870121363103882288', {'error': 'not-gs1'}], [']C10109147699409412219X9/BACAA-C1/9X19-B\x1d21/\x1d17759960', [['01', '09147699409412'], ['21', '9X9/BACAA-C1/9X19-B'], ['21', '/'], ['17', '759960']]], [']C01109918000653062932206451941', {'error': 'not-gs1'}], [']C017335622\x1d10/A/1X9\x1d1019911-1X/1B1/C-B\x1d400AX/C', {'error': 'not-gs1'}], [']C121-X-BCCC/AB/11/XX-C-B1A\x1d310310809321XX9-CB/X/XAB1XXC', {'error': 'length', 'ai': '21'}]]]
labels = ["regression: variable field maximum", "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: variable field maximum 0 | {'ai': '21', 'error': 'length'} | {'ai': '37', 'error': 'length'} | Failed |
| repair trap 1 | [['21', '/9A9-BBAXB9/1CX11A'], ['37', '0168'], ['400', 'XXXXACBAC1A99XX'], ['37', '958407873']] | {'ai': '37', 'error': 'length'} | Failed |
| combined fault 2 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 3 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 4 | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | Passed |
| boundary 5 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| boundary 6 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 7 | [['21', 'AC1CXBXC//BB1BCB'], ['3103', '278661'], ['37', '162541688'], ['37', '1']] | {'ai': '37', 'error': 'length'} | Failed |
SHA-256 / 7c54bdc18e9031a5115b35b3250b706a19a7d5b4bce335d8872e420c365de52d
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(s):
fixed_len = {'00': 18, '01': 14, '02': 14, '11': 6, '13': 6, '15': 6, '17': 6, '3103': 6}
var_max = {'10': 20, '21': 20, '30': 8, '37': 8, '400': 30}
if not s.startswith(']C1'):
return {'error': 'not-gs1'}
i = 3
out = []
while i < len(s):
if s[i] == '\x1d':
i += 1
continue
ai = None
for L in (2, 3, 4):
if s[i:i + L] in fixed_len or s[i:i + L] in var_max:
ai = s[i:i + L]
break
if ai is None:
return {'error': 'unknown-ai', 'at': i}
i += len(ai)
if ai in fixed_len:
n = fixed_len[ai]
val = s[i:i + n]
if len(val) != n or '\x1d' in val:
return {'error': 'short', 'ai': ai}
i += n
else:
j = s.find('\x1d', i)
if j == -1:
j = len(s)
val = s[i:j]
if not 1 <= len(val) <= var_max[ai]:
return {'error': 'length', 'ai': ai}
i = j
out.append([ai, val])
return out
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[']C137244121375\x1d21\x1d400XAXCC9C/XXB/1\x1d10/CA', {'error': 'length', 'ai': '37'}], [']C121/9A9-BBAXB9/1CX11A\x1d370168\x1d400XXXXACBAC1A99XX\x1d37958407873', {'error': 'length', 'ai': '37'}], [']C011400783', {'error': 'not-gs1'}], [']C03019\x1d10B9', {'error': 'not-gs1'}], [']C117140648306\x1d0141294680397442\x1d', [['17', '140648'], ['30', '6'], ['01', '41294680397442']]], [']d221B-1BA9-B\x1d219X91//1X9-/1A-C\x1d10BBCB1-9/-/9//-/BC1-A-X\x1d21/ABXAX9C-CC/-\x1d', {'error': 'not-gs1'}], [']C0\x1d3028612956', {'error': 'not-gs1'}], [']C121AC1CXBXC//BB1BCB\x1d310327866137162541688\x1d371', {'error': 'length', 'ai': '37'}]], [[']C12191XXAXB/XX-B91A9-1X1A\x1d10CBAB1-B', {'error': 'length', 'ai': '21'}], [']C13103253004017432790047008137876520261\x1d', {'error': 'length', 'ai': '37'}], [']C13076330559\x1d017350710908563810CX/1/1X//XX//AXCBA-\x1d30467914952', {'error': 'length', 'ai': '30'}], [']C04009\x1d10X-CXA1/X\x1d310311958730', {'error': 'not-gs1'}], [']C10044603095506351280311060380310300579483495402726338', {'error': 'unknown-ai', 'at': 41}], [']d211029205\x1d01139908024073283027281846\x1d10-X9C\x1d', {'error': 'not-gs1'}], [']C1310361473240011XBBC-1-CX1B-\x1d371255\x1d219X9B-C/', [['3103', '614732'], ['400', '11XBBC-1-CX1B-'], ['37', '1255'], ['21', '9X9B-C/']]], [']C137791221293\x1d400A11/1/ACC///CXC1CA/X-\x1d400A-/\x1d37768579', {'error': 'length', 'ai': '37'}]], [[']C121CX1CBA11//99A\x1d018138092042504821XCAA9BX9C91BXBX--B1B-\x1d3103153253', {'error': 'length', 'ai': '21'}], [']C1370404\x1d0169587500743493400C-B1-BAAC9AXXCXAA/B1X\x1d', [['37', '0404'], ['01', '69587500743493'], ['400', 'C-B1-BAAC9AXXCXAA/B1X']]], [']C137364\x1d37951579975\x1d11440863\x1d37038364119\x1d', {'error': 'length', 'ai': '37'}], [']C111362276', [['11', '362276']]], [']C121C-\x1d3103238166', [['21', 'C-'], ['3103', '238166']]], [']C121-/1-X-9B\x1d17420369015026678280984317842704\x1d', [['21', '-/1-X-9B'], ['17', '420369'], ['01', '50266782809843'], ['17', '842704']]], [']C111990558117862\x1d10X-11\x1d0141668383672539', {'error': 'short', 'ai': '11'}], [']C10011511945802272876110ABXB-BA1-B/1X1-BBCXCX1\x1d0143358957494055', {'error': 'length', 'ai': '10'}]], [[']C10153009609031376219XBB-1C-1A9//\x1d1781184810CB9CX-AX--B9ABCCBB9X-C\x1d', {'error': 'length', 'ai': '10'}], [']C121AB/-C9A99/\x1d305405245\x1d00419461779691996360400-1XBCX9CCA9/A-9-1C-11C\x1d', [['21', 'AB/-C9A99/'], ['30', '5405245'], ['00', '419461779691996360'], ['400', '-1XBCX9CCA9/A-9-1C-11C']]], [']C111141665\x1d37247204674\x1d37790824985\x1d00445616335895473473', {'error': 'length', 'ai': '37'}], [']C1211\x1d400/B-\x1d3067920\x1d', [['21', '1'], ['400', '/B-'], ['30', '67920']]], [']C1211CXX-B1B9XXX-/', [['21', '1CXX-B1B9XXX-/']]], [']C1308705431', [['30', '8705431']]], [']C010/ACC1C1C/9\x1d109\x1d00997634519263772689', {'error': 'not-gs1'}], [']C1211\x1d37789365790\x1d30311652\x1d', {'error': 'length', 'ai': '37'}]], [[']C13066\x1d37793432856\x1d3097076472', {'error': 'length', 'ai': '37'}], [']C137505172476\x1d3103210156', {'error': 'length', 'ai': '37'}], [']C137335719723\x1d', {'error': 'length', 'ai': '37'}], [']C037218164131\x1d017878870121363103882288', {'error': 'not-gs1'}], [']C10109147699409412219X9/BACAA-C1/9X19-B\x1d21/\x1d17759960', [['01', '09147699409412'], ['21', '9X9/BACAA-C1/9X19-B'], ['21', '/'], ['17', '759960']]], [']C01109918000653062932206451941', {'error': 'not-gs1'}], [']C017335622\x1d10/A/1X9\x1d1019911-1X/1B1/C-B\x1d400AX/C', {'error': 'not-gs1'}], [']C121-X-BCCC/AB/11/XX-C-B1A\x1d310310809321XX9-CB/X/XAB1XXC', {'error': 'length', 'ai': '21'}]]]
labels = ["regression: variable field maximum", "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: variable field maximum 0 | {'ai': '37', 'error': 'length'} | {'ai': '37', 'error': 'length'} | Passed |
| repair trap 1 | {'ai': '37', 'error': 'length'} | {'ai': '37', 'error': 'length'} | Passed |
| combined fault 2 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 3 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 4 | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | [['17', '140648'], ['30', '6'], ['01', '41294680397442']] | Passed |
| boundary 5 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| boundary 6 | {'error': 'not-gs1'} | {'error': 'not-gs1'} | Passed |
| control 7 | {'ai': '37', 'error': 'length'} | {'ai': '37', 'error': 'length'} | Passed |
SHA-256 / 38ab56dfe9afffdf9ae1a3f407e464cee20c570ee5dec05fdabad5f192a8357d
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 2026-09-29T14:49:46.299101+00:00.
Case digest / 6b3123fb3bd83c60e7299dad89092dcc3144fdd55060273c300104b7e3b38d7e