{"id":"W2394841101","doi":"10.1109/saner.2016.56","title":"Defect Prediction: Accomplishments and Future Challenges","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Software quality assurance; Software; Software quality; Software development; Software engineering; Quality (philosophy); Software metric; Data science; Software quality analyst; Key (lock); Field (mathematics); Prioritization; Risk analysis (engineering); Management science; Engineering; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001353725,0.00005836921,0.00005020477,0.00005240857,0.000033574,0.00004461654,0.0002839286,0.00002763703,0.00002872691],"category_scores_gemma":[0.0000444756,0.00003470149,0.00001789068,0.0000771343,0.00001494721,0.0003206506,0.0001949096,0.00003998466,0.00004807028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001840595,"about_ca_system_score_gemma":0.000009841358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.065997e-7,"about_ca_topic_score_gemma":5.753344e-7,"domain_scores_codex":[0.9993694,0.00001369896,0.00005257313,0.0002307036,0.0001788528,0.000154701],"domain_scores_gemma":[0.9993786,0.0002051728,0.000007070594,0.0003063722,0.00002841033,0.00007435588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00000198419,0.00001922689,0.01961762,0.00001385994,0.00002505927,0.000007803634,0.0001439535,6.172705e-7,0.0003735564,0.02681587,0.00890607,0.9440744],"study_design_scores_gemma":[0.0005440592,0.0001217843,0.7476174,0.00002951349,0.000001708807,0.00005442868,0.00001632523,0.0004097596,0.0007264911,0.001173742,0.2491411,0.0001637892],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09987586,0.007943034,0.788617,0.08670813,0.002522697,0.0004185051,0.000006525623,0.003108677,0.01079957],"genre_scores_gemma":[0.9802712,0.002069902,0.01640267,0.0001844012,0.0003818966,0.0000255391,2.186382e-7,0.00001044643,0.0006537758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9439106,"threshold_uncertainty_score":0.1415085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02160372313132453,"score_gpt":0.2460218626394165,"score_spread":0.2244181395080919,"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."}}