{"abstract":"Blocks with erasures are biased towards 0.","category":"Error-correcting codes","checks":8,"contract":"Decode an n-fold repetition code sent in contiguous blocks of n symbols; each received symbol is 0, 1 or None (erasure). Erasures do not vote. The bit is the majority of non-erased symbols; a tie (including an all-erased block) yields None. fixed_count counts non-erased symbols outvoted in decided blocks. A length that is not a multiple of n, or n < 1, returns None. Return [bits, fixed_count].","evaluation_group":"w2-error_correcting_codes-repetition-erasures","failed_approach":"Keeping only truthy symbols removes zeros as well as erasures.","family":"w2-error_correcting_codes-repetition-erasures-erasure-vote","id":"FA-71886","implementations":{"attempt":{"sha256":"029f2119e83c7671f571e3ca899d54e4af0fc51ad374ecbf2ade5772d614772d","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(r, n):\n    if n < 1 or len(r) % n:\n        return None\n    out, fixed_count = [], 0\n    for g in range(0, len(r), n):\n        grp = [x for x in r[g:g + n] if x]\n        ones = sum(grp)\n        zeros = len(grp) - ones\n        if ones == zeros:\n            out.append(None)\n            continue\n        b = 1 if ones > zeros else 0\n        out.append(b)\n        fixed_count += min(ones, zeros)\n    return [out, fixed_count]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, null, 1], 3]', [[0, None, 1], 3], [[None], 0]], ['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['partial-repair [[1, 1, 0], 3]', [[1, 1, 0], 3], [[1], 1]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]], [['regression [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]], ['regression [[1, 1, null, 0, 1, null, 0, null], 2]', [[1, 1, None, 0, 1, None, 0, None], 2], [[1, 0, 1, 0], 0]], ['partial-repair [[0, 0, null, null], 4]', [[0, 0, None, None], 4], [[0], 0]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['control [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]]], [['regression [[1, null, 0], 3]', [[1, None, 0], 3], [[None], 0]], ['regression [[null, null, null], 3]', [[None, None, None], 3], [[None], 0]], ['partial-repair [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['partial-repair [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]]], [['regression [[0, null, 1, 1, 1], 5]', [[0, None, 1, 1, 1], 5], [[1], 1]], ['regression [[null, 0, 1, 0, null, 1], 3]', [[None, 0, 1, 0, None, 1], 3], [[None, None], 0]], ['partial-repair [[1, 0, 0, 1, 1, 0], 3]', [[1, 0, 0, 1, 1, 0], 3], [[0, 1], 2]], ['partial-repair [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]]], [['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['regression [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['partial-repair [[1, 0], 2]', [[1, 0], 2], [[None], 0]], ['partial-repair [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"982a4e6fd40a82e6e4d7def36f673e244015abfe6cb21fbd581903883368a44b","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(r, n):\n    if n < 1 or len(r) % n:\n        return None\n    out, fixed_count = [], 0\n    for g in range(0, len(r), n):\n        grp = [x or 0 for x in r[g:g + n]]\n        ones = sum(grp)\n        zeros = len(grp) - ones\n        if ones == zeros:\n            out.append(None)\n            continue\n        b = 1 if ones > zeros else 0\n        out.append(b)\n        fixed_count += min(ones, zeros)\n    return [out, fixed_count]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, null, 1], 3]', [[0, None, 1], 3], [[None], 0]], ['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['partial-repair [[1, 1, 0], 3]', [[1, 1, 0], 3], [[1], 1]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]], [['regression [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]], ['regression [[1, 1, null, 0, 1, null, 0, null], 2]', [[1, 1, None, 0, 1, None, 0, None], 2], [[1, 0, 1, 0], 0]], ['partial-repair [[0, 0, null, null], 4]', [[0, 0, None, None], 4], [[0], 0]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['control [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]]], [['regression [[1, null, 0], 3]', [[1, None, 0], 3], [[None], 0]], ['regression [[null, null, null], 3]', [[None, None, None], 3], [[None], 0]], ['partial-repair [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['partial-repair [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]]], [['regression [[0, null, 1, 1, 1], 5]', [[0, None, 1, 1, 1], 5], [[1], 1]], ['regression [[null, 0, 1, 0, null, 1], 3]', [[None, 0, 1, 0, None, 1], 3], [[None, None], 0]], ['partial-repair [[1, 0, 0, 1, 1, 0], 3]', [[1, 0, 0, 1, 1, 0], 3], [[0, 1], 2]], ['partial-repair [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]]], [['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['regression [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['partial-repair [[1, 0], 2]', [[1, 0], 2], [[None], 0]], ['partial-repair [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"c73e596a3282473f6630001674ff08842ed51f609d8c660a83a5567a509e1154","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(r, n):\n    if n < 1 or len(r) % n:\n        return None\n    out, fixed_count = [], 0\n    for g in range(0, len(r), n):\n        grp = [x for x in r[g:g + n] if x is not None]\n        ones = sum(grp)\n        zeros = len(grp) - ones\n        if ones == zeros:\n            out.append(None)\n            continue\n        b = 1 if ones > zeros else 0\n        out.append(b)\n        fixed_count += min(ones, zeros)\n    return [out, fixed_count]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, null, 1], 3]', [[0, None, 1], 3], [[None], 0]], ['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['partial-repair [[1, 1, 0], 3]', [[1, 1, 0], 3], [[1], 1]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]], [['regression [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]], ['regression [[1, 1, null, 0, 1, null, 0, null], 2]', [[1, 1, None, 0, 1, None, 0, None], 2], [[1, 0, 1, 0], 0]], ['partial-repair [[0, 0, null, null], 4]', [[0, 0, None, None], 4], [[0], 0]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['control [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]]], [['regression [[1, null, 0], 3]', [[1, None, 0], 3], [[None], 0]], ['regression [[null, null, null], 3]', [[None, None, None], 3], [[None], 0]], ['partial-repair [[1, 0, null, null, 1, 1], 3]', [[1, 0, None, None, 1, 1], 3], [[None, 1], 0]], ['partial-repair [[0, 1, null, 0, 0, 1, 0, 0, 0, 0], 5]', [[0, 1, None, 0, 0, 1, 0, 0, 0, 0], 5], [[0, 0], 2]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]]], [['regression [[0, null, 1, 1, 1], 5]', [[0, None, 1, 1, 1], 5], [[1], 1]], ['regression [[null, 0, 1, 0, null, 1], 3]', [[None, 0, 1, 0, None, 1], 3], [[None, None], 0]], ['partial-repair [[1, 0, 0, 1, 1, 0], 3]', [[1, 0, 0, 1, 1, 0], 3], [[0, 1], 2]], ['partial-repair [[0, 1, 1, 1, 0, 0, null, 1], 4]', [[0, 1, 1, 1, 0, 0, None, 1], 4], [[1, 0], 2]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]]], [['regression [[1, 1, null], 3]', [[1, 1, None], 3], [[1], 0]], ['regression [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]', [[1, 1, 0, None, 0, None, 0, 0, 0, 1], 5], [[None, 0], 1]], ['partial-repair [[1, 0], 2]', [[1, 0], 2], [[None], 0]], ['partial-repair [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3]', [[1, 1, 0, 0, 0, 1, 1, 1, 0], 3], [[1, 0, 1], 3]], ['control [[], 3]', [[], 3], [[], 0]], ['control [[1], 1]', [[1], 1], [[1], 0]], ['control [[1, 1], 3]', [[1, 1], 3], None], ['control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]', [[0, 1, 0, 1, 0, None, 1, 0, 1, 1], 5], [[0, 1], 3]]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"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.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-error_correcting_codes-repetition-erasures-erasure-vote","generated_at":"2026-09-29T14:48:33.570817+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Robust control channels repeat critical flags and must treat erased symbols differently from zeros.","repair":"Drop erasures from the vote entirely.","root_cause":"Erased symbols are converted to 0 before voting.","sha256":"ff855f5f4a9d5ae7aab1a968c17baa6c3ed7590f487dca636506985972bad75c","title":"Repetition decoder counts erasures as zeros · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":36.77,"exit_code":1,"observations":[{"actual":[[1],0],"check":"regression [[0, null, 1], 3]","expected":[[null],0],"passed":false},{"actual":[[1],0],"check":"regression [[1, 1, null], 3]","expected":[[1],0],"passed":true},{"actual":[[1],0],"check":"partial-repair [[1, 1, 0], 3]","expected":[[1],1],"passed":false},{"actual":[[1],0],"check":"control [[1], 1]","expected":[[1],0],"passed":true},{"actual":null,"check":"control [[1, 1], 3]","expected":null,"passed":true},{"actual":[[],0],"check":"control [[], 3]","expected":[[],0],"passed":true},{"actual":[[1,1],0],"check":"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]","expected":[[null,0],1],"passed":false},{"actual":[[1,1],0],"check":"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]","expected":[[0,1],3],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression [[0, null, 1], 3]\", \"actual\": [[1], 0], \"expected\": [[null], 0], \"passed\": false}, {\"check\": \"regression [[1, 1, null], 3]\", \"actual\": [[1], 0], \"expected\": [[1], 0], \"passed\": true}, {\"check\": \"partial-repair [[1, 1, 0], 3]\", \"actual\": [[1], 0], \"expected\": [[1], 1], \"passed\": false}, {\"check\": \"control [[1], 1]\", \"actual\": [[1], 0], \"expected\": [[1], 0], \"passed\": true}, {\"check\": \"control [[1, 1], 3]\", \"actual\": null, \"expected\": null, \"passed\": true}, {\"check\": \"control [[], 3]\", \"actual\": [[], 0], \"expected\": [[], 0], \"passed\": true}, {\"check\": \"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]\", \"actual\": [[1, 1], 0], \"expected\": [[null, 0], 1], \"passed\": false}, {\"check\": \"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]\", \"actual\": [[1, 1], 0], \"expected\": [[0, 1], 3], \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":37.221,"exit_code":1,"observations":[{"actual":[[0],1],"check":"regression [[0, null, 1], 3]","expected":[[null],0],"passed":false},{"actual":[[1],1],"check":"regression [[1, 1, null], 3]","expected":[[1],0],"passed":false},{"actual":[[1],1],"check":"partial-repair [[1, 1, 0], 3]","expected":[[1],1],"passed":true},{"actual":[[1],0],"check":"control [[1], 1]","expected":[[1],0],"passed":true},{"actual":null,"check":"control [[1, 1], 3]","expected":null,"passed":true},{"actual":[[],0],"check":"control [[], 3]","expected":[[],0],"passed":true},{"actual":[[0,0],3],"check":"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]","expected":[[null,0],1],"passed":false},{"actual":[[0,1],4],"check":"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]","expected":[[0,1],3],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression [[0, null, 1], 3]\", \"actual\": [[0], 1], \"expected\": [[null], 0], \"passed\": false}, {\"check\": \"regression [[1, 1, null], 3]\", \"actual\": [[1], 1], \"expected\": [[1], 0], \"passed\": false}, {\"check\": \"partial-repair [[1, 1, 0], 3]\", \"actual\": [[1], 1], \"expected\": [[1], 1], \"passed\": true}, {\"check\": \"control [[1], 1]\", \"actual\": [[1], 0], \"expected\": [[1], 0], \"passed\": true}, {\"check\": \"control [[1, 1], 3]\", \"actual\": null, \"expected\": null, \"passed\": true}, {\"check\": \"control [[], 3]\", \"actual\": [[], 0], \"expected\": [[], 0], \"passed\": true}, {\"check\": \"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]\", \"actual\": [[0, 0], 3], \"expected\": [[null, 0], 1], \"passed\": false}, {\"check\": \"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]\", \"actual\": [[0, 1], 4], \"expected\": [[0, 1], 3], \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":36.931,"exit_code":0,"observations":[{"actual":[[null],0],"check":"regression [[0, null, 1], 3]","expected":[[null],0],"passed":true},{"actual":[[1],0],"check":"regression [[1, 1, null], 3]","expected":[[1],0],"passed":true},{"actual":[[1],1],"check":"partial-repair [[1, 1, 0], 3]","expected":[[1],1],"passed":true},{"actual":[[1],0],"check":"control [[1], 1]","expected":[[1],0],"passed":true},{"actual":null,"check":"control [[1, 1], 3]","expected":null,"passed":true},{"actual":[[],0],"check":"control [[], 3]","expected":[[],0],"passed":true},{"actual":[[null,0],1],"check":"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]","expected":[[null,0],1],"passed":true},{"actual":[[0,1],3],"check":"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]","expected":[[0,1],3],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression [[0, null, 1], 3]\", \"actual\": [[null], 0], \"expected\": [[null], 0], \"passed\": true}, {\"check\": \"regression [[1, 1, null], 3]\", \"actual\": [[1], 0], \"expected\": [[1], 0], \"passed\": true}, {\"check\": \"partial-repair [[1, 1, 0], 3]\", \"actual\": [[1], 1], \"expected\": [[1], 1], \"passed\": true}, {\"check\": \"control [[1], 1]\", \"actual\": [[1], 0], \"expected\": [[1], 0], \"passed\": true}, {\"check\": \"control [[1, 1], 3]\", \"actual\": null, \"expected\": null, \"passed\": true}, {\"check\": \"control [[], 3]\", \"actual\": [[], 0], \"expected\": [[], 0], \"passed\": true}, {\"check\": \"control [[1, 1, 0, null, 0, null, 0, 0, 0, 1], 5]\", \"actual\": [[null, 0], 1], \"expected\": [[null, 0], 1], \"passed\": true}, {\"check\": \"control [[0, 1, 0, 1, 0, null, 1, 0, 1, 1], 5]\", \"actual\": [[0, 1], 3], \"expected\": [[0, 1], 3], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}