{"abstract":"Codewords fail to decode as clean.","category":"Error-correcting codes","checks":8,"contract":"Hamming(7,4) encoder: data d1..d4 go to positions 3, 5, 6, 7; the parity bit at position p (1, 2, 4) is the XOR of all other positions whose index has bit p set. Return the 7-bit codeword (position 1 first).","evaluation_group":"w2-error_correcting_codes-hamming74-encode","failed_approach":"Covering every position at or after p ignores the binary structure.","family":"w2-error_correcting_codes-hamming74-encode-coverage-rule","id":"FA-71861","implementations":{"attempt":{"sha256":"cef6e033bc938420524954cb461e74f999892c4b158a2f670f10305876b2e92b","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    d1, d2, d3, d4 = d\n    c = [0, 0, d1, 0, d2, d3, d4]\n    for p in (1, 2, 4):\n        v = 0\n        for pos in range(1, 8):\n            if pos >= p and pos != p:\n                v ^= c[pos - 1]\n        c[p - 1] = v\n    return c\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['regression [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]], [['regression [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['regression [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['partial-repair [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['control [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['control [[1, 0, 0, 1]]', [[1, 0, 0, 1]], [0, 0, 1, 1, 0, 0, 1]], ['control [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]]], [['regression [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['regression [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['partial-repair [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['partial-repair [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[1, 1, 0, 0]]', [[1, 1, 0, 0]], [0, 1, 1, 1, 1, 0, 0]], ['control [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['control [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]]], [['regression [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['regression [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['partial-repair [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['partial-repair [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['control [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['control [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]]], [['regression [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['regression [[1, 1, 1, 1]]', [[1, 1, 1, 1]], [1, 1, 1, 1, 1, 1, 1]], ['partial-repair [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]]]\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":"73d73b2c428e25df798a1e9db10f922d4453226370a28cce79551ea8f6e53ddc","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    d1, d2, d3, d4 = d\n    c = [0, 0, d1, 0, d2, d3, d4]\n    for p in (1, 2, 4):\n        v = 0\n        for pos in range(1, 8):\n            if pos % p == 0 and pos != p:\n                v ^= c[pos - 1]\n        c[p - 1] = v\n    return c\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['regression [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]], [['regression [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['regression [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['partial-repair [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['control [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['control [[1, 0, 0, 1]]', [[1, 0, 0, 1]], [0, 0, 1, 1, 0, 0, 1]], ['control [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]]], [['regression [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['regression [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['partial-repair [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['partial-repair [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[1, 1, 0, 0]]', [[1, 1, 0, 0]], [0, 1, 1, 1, 1, 0, 0]], ['control [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['control [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]]], [['regression [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['regression [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['partial-repair [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['partial-repair [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['control [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['control [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]]], [['regression [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['regression [[1, 1, 1, 1]]', [[1, 1, 1, 1]], [1, 1, 1, 1, 1, 1, 1]], ['partial-repair [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]]]\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":"a398373379e46b6b15a432faa20844e17ee71cbf16437f284e99d85d3fe701d8","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(d):\n    d1, d2, d3, d4 = d\n    c = [0, 0, d1, 0, d2, d3, d4]\n    for p in (1, 2, 4):\n        v = 0\n        for pos in range(1, 8):\n            if pos & p and pos != p:\n                v ^= c[pos - 1]\n        c[p - 1] = v\n    return c\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['regression [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]], [['regression [[0, 1, 0, 0]]', [[0, 1, 0, 0]], [1, 0, 0, 1, 1, 0, 0]], ['regression [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['partial-repair [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['control [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['control [[1, 0, 0, 1]]', [[1, 0, 0, 1]], [0, 0, 1, 1, 0, 0, 1]], ['control [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]]], [['regression [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]], ['regression [[1, 0, 0, 0]]', [[1, 0, 0, 0]], [1, 1, 1, 0, 0, 0, 0]], ['partial-repair [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['partial-repair [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[1, 1, 0, 0]]', [[1, 1, 0, 0]], [0, 1, 1, 1, 1, 0, 0]], ['control [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['control [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]]], [['regression [[1, 0, 1, 0]]', [[1, 0, 1, 0]], [1, 0, 1, 1, 0, 1, 0]], ['regression [[1, 0, 1, 1]]', [[1, 0, 1, 1]], [0, 1, 1, 0, 0, 1, 1]], ['partial-repair [[1, 1, 0, 1]]', [[1, 1, 0, 1]], [1, 0, 1, 0, 1, 0, 1]], ['partial-repair [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 0, 0, 1]]', [[0, 0, 0, 1]], [1, 1, 0, 1, 0, 0, 1]], ['control [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['control [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]]], [['regression [[1, 1, 1, 0]]', [[1, 1, 1, 0]], [0, 0, 1, 0, 1, 1, 0]], ['regression [[1, 1, 1, 1]]', [[1, 1, 1, 1]], [1, 1, 1, 1, 1, 1, 1]], ['partial-repair [[0, 0, 1, 0]]', [[0, 0, 1, 0]], [0, 1, 0, 1, 0, 1, 0]], ['partial-repair [[0, 0, 1, 1]]', [[0, 0, 1, 1]], [1, 0, 0, 0, 0, 1, 1]], ['control [[0, 0, 0, 0]]', [[0, 0, 0, 0]], [0, 0, 0, 0, 0, 0, 0]], ['control [[0, 1, 0, 1]]', [[0, 1, 0, 1]], [0, 1, 0, 0, 1, 0, 1]], ['control [[0, 1, 1, 0]]', [[0, 1, 1, 0]], [1, 1, 0, 0, 1, 1, 0]], ['control [[0, 1, 1, 1]]', [[0, 1, 1, 1]], [0, 0, 0, 1, 1, 1, 1]]]]\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-hamming74-encode-coverage-rule","generated_at":"2026-09-29T14:48:33.448843+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Low-cost telemetry links protect nibbles with Hamming(7,4).","repair":"A parity bit at p covers exactly the positions whose index has bit p set.","root_cause":"Coverage is tested with pos % p == 0 instead of the binary membership pos & p.","sha256":"fc113ca0cc480470c14c579c6d9c8af8f2c66e2615858e24fc9865e6432e9ea8","title":"Hamming encoder parity covers multiples of the parity position · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":38.737,"exit_code":1,"observations":[{"actual":[1,1,0,1,0,0,1],"check":"regression [[0, 0, 0, 1]]","expected":[1,1,0,1,0,0,1],"passed":true},{"actual":[1,1,0,1,0,1,0],"check":"regression [[0, 0, 1, 0]]","expected":[0,1,0,1,0,1,0],"passed":false},{"actual":[0,0,0,0,0,1,1],"check":"partial-repair [[0, 0, 1, 1]]","expected":[1,0,0,0,0,1,1],"passed":false},{"actual":[0,0,0,0,0,0,0],"check":"control [[0, 0, 0, 0]]","expected":[0,0,0,0,0,0,0],"passed":true},{"actual":[1,1,0,1,1,0,0],"check":"control [[0, 1, 0, 0]]","expected":[1,0,0,1,1,0,0],"passed":false},{"actual":[0,0,0,0,1,0,1],"check":"control [[0, 1, 0, 1]]","expected":[0,1,0,0,1,0,1],"passed":false},{"actual":[0,0,0,0,1,1,0],"check":"control [[0, 1, 1, 0]]","expected":[1,1,0,0,1,1,0],"passed":false},{"actual":[1,1,0,1,1,1,1],"check":"control [[0, 1, 1, 1]]","expected":[0,0,0,1,1,1,1],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression [[0, 0, 0, 1]]\", \"actual\": [1, 1, 0, 1, 0, 0, 1], \"expected\": [1, 1, 0, 1, 0, 0, 1], \"passed\": true}, {\"check\": \"regression [[0, 0, 1, 0]]\", \"actual\": [1, 1, 0, 1, 0, 1, 0], \"expected\": [0, 1, 0, 1, 0, 1, 0], \"passed\": false}, {\"check\": \"partial-repair [[0, 0, 1, 1]]\", \"actual\": [0, 0, 0, 0, 0, 1, 1], \"expected\": [1, 0, 0, 0, 0, 1, 1], \"passed\": false}, {\"check\": \"control [[0, 0, 0, 0]]\", \"actual\": [0, 0, 0, 0, 0, 0, 0], \"expected\": [0, 0, 0, 0, 0, 0, 0], \"passed\": true}, {\"check\": \"control [[0, 1, 0, 0]]\", \"actual\": [1, 1, 0, 1, 1, 0, 0], \"expected\": [1, 0, 0, 1, 1, 0, 0], \"passed\": false}, {\"check\": \"control [[0, 1, 0, 1]]\", \"actual\": [0, 0, 0, 0, 1, 0, 1], \"expected\": [0, 1, 0, 0, 1, 0, 1], \"passed\": false}, {\"check\": \"control [[0, 1, 1, 0]]\", \"actual\": [0, 0, 0, 0, 1, 1, 0], \"expected\": [1, 1, 0, 0, 1, 1, 0], \"passed\": false}, {\"check\": \"control [[0, 1, 1, 1]]\", \"actual\": [1, 1, 0, 1, 1, 1, 1], \"expected\": [0, 0, 0, 1, 1, 1, 1], \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.042,"exit_code":1,"observations":[{"actual":[1,0,0,0,0,0,1],"check":"regression [[0, 0, 0, 1]]","expected":[1,1,0,1,0,0,1],"passed":false},{"actual":[1,1,0,0,0,1,0],"check":"regression [[0, 0, 1, 0]]","expected":[0,1,0,1,0,1,0],"passed":false},{"actual":[0,1,0,0,0,1,1],"check":"partial-repair [[0, 0, 1, 1]]","expected":[1,0,0,0,0,1,1],"passed":false},{"actual":[0,0,0,0,0,0,0],"check":"control [[0, 0, 0, 0]]","expected":[0,0,0,0,0,0,0],"passed":true},{"actual":[1,0,0,0,1,0,0],"check":"control [[0, 1, 0, 0]]","expected":[1,0,0,1,1,0,0],"passed":false},{"actual":[0,0,0,0,1,0,1],"check":"control [[0, 1, 0, 1]]","expected":[0,1,0,0,1,0,1],"passed":false},{"actual":[0,1,0,0,1,1,0],"check":"control [[0, 1, 1, 0]]","expected":[1,1,0,0,1,1,0],"passed":false},{"actual":[1,1,0,0,1,1,1],"check":"control [[0, 1, 1, 1]]","expected":[0,0,0,1,1,1,1],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression [[0, 0, 0, 1]]\", \"actual\": [1, 0, 0, 0, 0, 0, 1], \"expected\": [1, 1, 0, 1, 0, 0, 1], \"passed\": false}, {\"check\": \"regression [[0, 0, 1, 0]]\", \"actual\": [1, 1, 0, 0, 0, 1, 0], \"expected\": [0, 1, 0, 1, 0, 1, 0], \"passed\": false}, {\"check\": \"partial-repair [[0, 0, 1, 1]]\", \"actual\": [0, 1, 0, 0, 0, 1, 1], \"expected\": [1, 0, 0, 0, 0, 1, 1], \"passed\": false}, {\"check\": \"control [[0, 0, 0, 0]]\", \"actual\": [0, 0, 0, 0, 0, 0, 0], \"expected\": [0, 0, 0, 0, 0, 0, 0], \"passed\": true}, {\"check\": \"control [[0, 1, 0, 0]]\", \"actual\": [1, 0, 0, 0, 1, 0, 0], \"expected\": [1, 0, 0, 1, 1, 0, 0], \"passed\": false}, {\"check\": \"control [[0, 1, 0, 1]]\", \"actual\": [0, 0, 0, 0, 1, 0, 1], \"expected\": [0, 1, 0, 0, 1, 0, 1], \"passed\": false}, {\"check\": \"control [[0, 1, 1, 0]]\", \"actual\": [0, 1, 0, 0, 1, 1, 0], \"expected\": [1, 1, 0, 0, 1, 1, 0], \"passed\": false}, {\"check\": \"control [[0, 1, 1, 1]]\", \"actual\": [1, 1, 0, 0, 1, 1, 1], \"expected\": [0, 0, 0, 1, 1, 1, 1], \"passed\": false}], \"passed\": false}\n"},"fixed":{"elapsed_ms":37.762,"exit_code":0,"observations":[{"actual":[1,1,0,1,0,0,1],"check":"regression [[0, 0, 0, 1]]","expected":[1,1,0,1,0,0,1],"passed":true},{"actual":[0,1,0,1,0,1,0],"check":"regression [[0, 0, 1, 0]]","expected":[0,1,0,1,0,1,0],"passed":true},{"actual":[1,0,0,0,0,1,1],"check":"partial-repair [[0, 0, 1, 1]]","expected":[1,0,0,0,0,1,1],"passed":true},{"actual":[0,0,0,0,0,0,0],"check":"control [[0, 0, 0, 0]]","expected":[0,0,0,0,0,0,0],"passed":true},{"actual":[1,0,0,1,1,0,0],"check":"control [[0, 1, 0, 0]]","expected":[1,0,0,1,1,0,0],"passed":true},{"actual":[0,1,0,0,1,0,1],"check":"control [[0, 1, 0, 1]]","expected":[0,1,0,0,1,0,1],"passed":true},{"actual":[1,1,0,0,1,1,0],"check":"control [[0, 1, 1, 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