{"id":"W2127483730","doi":"10.1016/j.infsof.2014.03.005","title":"Toward automated feature model configuration with optimizing non-functional requirements","year":2014,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; Athabasca University; Simon Fraser University","funders":"","keywords":"Feature model; Feature (linguistics); Computer science; Interdependence; Software product line; Data mining; Process (computing); Functional requirement; Functional dependency; Hierarchy; Artificial intelligence; Machine learning; Software; Software engineering; Software development","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":[0.0009282575,0.001304154,0.0006903674,0.001316163,0.0005328445,0.001584329,0.001526182,0.001024284,0.003399873],"category_scores_gemma":[0.005085639,0.0007883688,0.001178925,0.0009486652,0.0006273029,0.001815252,0.001649908,0.001210769,0.001349265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008201141,"about_ca_system_score_gemma":0.001518564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002828293,"about_ca_topic_score_gemma":0.007009954,"domain_scores_codex":[0.9982964,0.0004794382,0.00007781281,0.0002257303,0.0007684538,0.0001521355],"domain_scores_gemma":[0.9978446,0.0007958085,0.0002047947,0.000717161,0.0003956601,0.00004192746],"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":[0.0002478404,0.0003244953,0.003772799,0.0002590778,0.0000973148,0.0004868924,0.0002932117,0.3842882,0.07175157,0.02152723,0.006422063,0.5105293],"study_design_scores_gemma":[0.00002136915,0.00006519427,0.0005134915,0.00001662283,0.00003128571,0.0001201086,0.00007444213,0.9659564,0.01990731,0.01070474,0.002573786,0.00001512847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02632327,0.00005968852,0.9647119,0.0001076197,0.00001481937,0.0000966277,0.0001005028,0.005029507,0.003556081],"genre_scores_gemma":[0.3506213,0.00006768545,0.6460261,0.00008261561,0.0000116748,0.0001101904,0.0004112389,0.0007727301,0.001896456],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003399873,"threshold_uncertainty_score":0.0113737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02434571316413649,"score_gpt":0.2529423929075516,"score_spread":0.2285966797434151,"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."}}