{"id":"W2158344808","doi":"10.1109/ictai.2009.110","title":"Using Concepts Analysis for Mining Functional Features from Legacy Code","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Implementation; Code (set theory); Legacy system; Programming language; Legacy code; Inheritance (genetic algorithm); Software engineering; Source code; Software","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":[0.002493041,0.001105808,0.0005799814,0.01590455,0.00107284,0.001541786,0.001439672,0.0009091967,0.001131451],"category_scores_gemma":[0.01504676,0.0004294178,0.001198313,0.005868323,0.001202479,0.002768999,0.001486586,0.0009007495,0.0004081913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061952,"about_ca_system_score_gemma":0.002480366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005832165,"about_ca_topic_score_gemma":0.005777392,"domain_scores_codex":[0.9982033,0.0003009865,0.0002247585,0.0004568612,0.0007070123,0.0001069829],"domain_scores_gemma":[0.9886975,0.006770411,0.001492213,0.0009323761,0.001834946,0.0002725077],"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":[0.000353511,0.0005665777,0.101853,0.001922517,0.0002850955,0.002876329,0.007426094,0.02284711,0.03089773,0.02993762,0.004185904,0.7968485],"study_design_scores_gemma":[0.0002546753,0.001059758,0.1205659,0.0008856167,0.0006734096,0.00610855,0.007287098,0.6157042,0.07088182,0.1210992,0.05503711,0.0004426545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2643392,0.001053842,0.7247508,0.0003448855,0.00003215614,0.001008145,0.003003654,0.002505541,0.00296169],"genre_scores_gemma":[0.2681502,0.000283787,0.7257369,0.00005664336,0.00002345232,0.0007011589,0.004216471,0.0001586242,0.0006727409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01590455,"threshold_uncertainty_score":0.01318461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06712511127362189,"score_gpt":0.3440860700126813,"score_spread":0.2769609587390593,"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."}}