{"id":"W2046835698","doi":"10.1109/wicsa.2014.27","title":"Deriving Component Interfaces after a Restructuring of a Legacy System","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Component (thermodynamics); Consistency (knowledge bases); Programming language; Set (abstract data type); Class (philosophy); Object-oriented programming; Perspective (graphical); Component-based software engineering; Theoretical computer science; Restructuring; Software engineering; Software system; Software; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005676823,0.0003324891,0.0006276006,0.0002167966,0.00002954564,0.0001719185,0.001687364,0.0001850974,0.000003026669],"category_scores_gemma":[0.0002997807,0.0002938525,0.0001270394,0.0001022652,0.00005947655,0.0002742186,0.004437064,0.0004742295,0.000005479365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001349144,"about_ca_system_score_gemma":0.00004843757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004983164,"about_ca_topic_score_gemma":0.000003244542,"domain_scores_codex":[0.9980137,0.0002217262,0.0005273835,0.0006514363,0.0002846593,0.0003011429],"domain_scores_gemma":[0.9974698,0.0006447552,0.0003009594,0.00142673,0.00009226845,0.00006542173],"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":[0.00002571508,0.00002130833,0.0003514642,0.00523288,0.0001551688,0.00005671515,0.001961503,0.9493726,0.003609773,0.02030879,0.00003140497,0.01887264],"study_design_scores_gemma":[0.001095553,0.0003136908,0.03286941,0.01613819,0.0001281297,0.0003424595,0.0007810204,0.6156065,0.2684764,0.05930712,0.0005583422,0.004383094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1574412,0.0005062835,0.8390799,0.00003598485,0.001593727,0.0001832617,0.00000144114,0.001020182,0.0001379838],"genre_scores_gemma":[0.5155301,0.000005710036,0.4843587,0.000007003166,0.00003806095,0.00003069295,4.589431e-7,0.00001322805,0.00001604975],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3580889,"threshold_uncertainty_score":0.9999514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02553525872328578,"score_gpt":0.2702165479424661,"score_spread":0.2446812892191804,"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."}}