{"id":"W2034209539","doi":"10.1109/saner.2015.7081848","title":"CloCom: Mining existing source code for automatic comment generation","year":2015,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; KPI-driven code analysis; Code review; Program comprehension; Static program analysis; Source code; Codebase; Programming language; Code (set theory); Redundant code; Source lines of code; Software engineering; Software maintenance; Java; Maintainability; Code generation; Software; Dead code; Software development; Unreachable code; Software system; Operating system; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004897977,0.002815383,0.001105118,0.01261723,0.001219821,0.001531009,0.002445213,0.001875927,0.004290342],"category_scores_gemma":[0.0292253,0.000860566,0.001501748,0.004899941,0.0008480849,0.003190291,0.002638853,0.001566473,0.005209022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000945474,"about_ca_system_score_gemma":0.003218845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004724271,"about_ca_topic_score_gemma":0.0075379,"domain_scores_codex":[0.9941173,0.00143632,0.0004611935,0.001389448,0.002296187,0.0002995653],"domain_scores_gemma":[0.959591,0.01874542,0.003987669,0.005030553,0.01190799,0.0007373281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008225034,0.0007043596,0.02588609,0.004023719,0.0002973131,0.001828851,0.004406726,0.00567474,0.09657161,0.003769987,0.1117451,0.744269],"study_design_scores_gemma":[0.0005344689,0.001074752,0.0421293,0.000853477,0.0004235115,0.002900982,0.003850764,0.580829,0.1832109,0.01158064,0.172109,0.0005031439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07460733,0.0008598873,0.7130386,0.0009299806,0.0003181665,0.002766578,0.02307248,0.1802945,0.004112499],"genre_scores_gemma":[0.1237219,0.0003727042,0.8047761,0.0003549998,0.0001805611,0.001875963,0.05500977,0.008133342,0.005574561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01261723,"threshold_uncertainty_score":0.02590328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1587458887233859,"score_gpt":0.3454253794659993,"score_spread":0.1866794907426134,"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."}}