{"id":"W2743745531","doi":"10.18293/seke2017-056","title":"A Comparative Study of Software Bugs in Clone and Non-Clone Code","year":2017,"lang":"en","type":"article","venue":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"clone (Java method); Computer science; Programming language; Software bug; Software maintenance; Code (set theory); Software engineering; Software; Software development; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001920342,0.0002341309,0.0003409258,0.006706359,0.0003865943,0.0005846605,0.0003800718,0.0004970529,0.0009930823],"category_scores_gemma":[0.02716511,0.0001688305,0.0003135411,0.002344044,0.0008889608,0.001592145,0.0008756671,0.0003408224,0.0001526936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000355972,"about_ca_system_score_gemma":0.0002862754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001007489,"about_ca_topic_score_gemma":0.002098971,"domain_scores_codex":[0.9976469,0.0005446554,0.0002380356,0.0004655801,0.0008981655,0.0002067828],"domain_scores_gemma":[0.9435359,0.03212266,0.01336052,0.002196302,0.007022584,0.001762009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005701815,0.0001917348,0.9221179,0.0002668857,0.000130532,0.001046449,0.005910669,0.0003698816,0.009292574,0.0003505571,0.0002715351,0.05948108],"study_design_scores_gemma":[0.000009705995,0.0008947502,0.9915121,0.00003723666,0.00005102873,0.00172001,0.00210529,0.0009959734,0.001844627,0.0002066445,0.0006025432,0.00002006567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987848,0.000227934,0.0006022035,0.00001599097,0.000002987356,0.00001164837,0.00005757656,0.00002192117,0.0002749647],"genre_scores_gemma":[0.9986246,0.0001064004,0.0008628732,0.00001111651,0.000006250987,0.00001022465,0.0001711273,0.00001277805,0.0001946464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006706359,"threshold_uncertainty_score":0.01015586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02713572723070102,"score_gpt":0.2810914379011535,"score_spread":0.2539557106704525,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}