{"id":"W2592568457","doi":"10.1002/smr.1843","title":"MORE: A multi‐objective refactoring recommendation approach to introducing design patterns and fixing code smells","year":2017,"lang":"en","type":"article","venue":"Journal of Software Evolution and Process","topic":"Software Engineering Research","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Japan Society for the Promotion of Science; Science Foundation Ireland","keywords":"Code refactoring; Code smell; Computer science; Software quality; Software engineering; Maintainability; Class (philosophy); Software maintenance; Source code; Quality (philosophy); Software; Software system; Software development; Programming language; Artificial intelligence","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":[0.002349411,0.001819756,0.001322573,0.002740634,0.000553049,0.0009106529,0.002182197,0.00153802,0.002752136],"category_scores_gemma":[0.005115537,0.0007672471,0.001667159,0.001453804,0.000521513,0.001088699,0.0009248582,0.0009657154,0.0005678128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097136,"about_ca_system_score_gemma":0.001974682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008561646,"about_ca_topic_score_gemma":0.01617258,"domain_scores_codex":[0.9982462,0.0005845368,0.0001144047,0.000316452,0.0006115139,0.0001268808],"domain_scores_gemma":[0.9968618,0.001582126,0.0004212483,0.0002924484,0.0007180833,0.0001242559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001947964,0.0006784819,0.005983141,0.0005304173,0.0003640803,0.0002355618,0.0003957618,0.4923183,0.01296697,0.004199106,0.004690601,0.4774428],"study_design_scores_gemma":[0.00006724644,0.000241129,0.001239463,0.00003780957,0.0001175386,0.00008178122,0.00006975247,0.9908647,0.002292434,0.002444446,0.002513823,0.00002992895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04590047,0.000547445,0.9471709,0.000363327,0.00005580995,0.0003493932,0.0001982994,0.002617155,0.002797279],"genre_scores_gemma":[0.2898702,0.0003107505,0.7029045,0.0003836242,0.00004819808,0.0005283956,0.0006282323,0.0003158818,0.005010202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008561646,"threshold_uncertainty_score":0.01702362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04468082121305431,"score_gpt":0.3188694893080094,"score_spread":0.2741886680949551,"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."}}