{"id":"W1536265389","doi":"10.1007/3-540-46423-9_2","title":"Optimizing Java Bytecode Using the Soot Framework: Is It Feasible?","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":313,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bytecode; Java bytecode; Computer science; Java; Programming language; Java annotation; Class (philosophy); Generics in Java; Program optimization; Java applet; Operating system; Compiler; Artificial intelligence","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":[0.00115195,0.0009612363,0.001074208,0.0004554459,0.0004338395,0.001586468,0.001724411,0.000963838,0.005710925],"category_scores_gemma":[0.005253985,0.0005940288,0.0009196803,0.0007018499,0.000878086,0.004897524,0.0007802619,0.001545177,0.001876437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000525958,"about_ca_system_score_gemma":0.001530004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003691611,"about_ca_topic_score_gemma":0.005886809,"domain_scores_codex":[0.9986153,0.0003169234,0.00005612117,0.0001816018,0.0005206033,0.0003095644],"domain_scores_gemma":[0.9972768,0.0009661342,0.0001733229,0.0009676834,0.0005208286,0.00009518422],"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":[0.0009462987,0.0002950038,0.004262058,0.0005423957,0.0001749892,0.0001403301,0.0002016409,0.05462862,0.03080404,0.1070989,0.02414279,0.7767628],"study_design_scores_gemma":[0.0002590775,0.0004727968,0.003275601,0.000291982,0.0003147408,0.0003941937,0.0003251677,0.636728,0.07826398,0.2128261,0.06670976,0.0001386112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1023994,0.003654298,0.8342586,0.00356082,0.0005343759,0.00008674145,0.0002055446,0.02677541,0.02852483],"genre_scores_gemma":[0.5190296,0.002088822,0.4590565,0.0006420853,0.000158703,0.00008102616,0.0005033676,0.006222447,0.01221735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005710925,"threshold_uncertainty_score":0.01910496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05289934935660727,"score_gpt":0.3031957885134227,"score_spread":0.2502964391568154,"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."}}