{"id":"W2084979378","doi":"10.1145/568235.568237","title":"Dynamic analysis for reverse engineering and program understanding","year":2002,"lang":"en","type":"article","venue":"ACM SIGAPP Applied Computing Review","topic":"Software Engineering Research","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reverse engineering; Interoperation; Computer science; Software engineering; Legacy system; Program comprehension; Component (thermodynamics); Software maintenance; Systems engineering; Focus (optics); Software system; Data science; Software; Engineering; Interoperability; World Wide Web; Programming language","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":[0.0008154282,0.0002471805,0.0005293826,0.0002745973,0.0001518927,0.0001822521,0.001076257,0.00006314571,0.000009021569],"category_scores_gemma":[0.0007907414,0.0002481758,0.0001650112,0.002017317,0.00003012204,0.0001072078,0.0005780021,0.0002225599,0.00001543561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162921,"about_ca_system_score_gemma":0.00001194146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000171765,"about_ca_topic_score_gemma":4.662942e-7,"domain_scores_codex":[0.9981233,0.00002090806,0.0003740168,0.0006359788,0.0003091655,0.0005366157],"domain_scores_gemma":[0.9970858,0.001578838,0.0001028013,0.001025266,0.0000482472,0.0001591256],"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":[0.000004286402,0.000204941,0.001499483,0.01144554,0.001470895,0.00003022208,0.0007189018,0.01483938,0.0004808858,0.03997037,0.003578372,0.9257568],"study_design_scores_gemma":[0.0003268716,0.00005684296,0.0006191605,0.00100141,0.0002231448,0.00001544593,0.000008572767,0.9889122,0.00002104221,0.0005503126,0.007807534,0.0004575152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001402615,0.02199276,0.9736054,0.0006641923,0.00008887242,0.001252985,0.000001268682,0.0009227572,0.0000691633],"genre_scores_gemma":[0.566081,0.004504777,0.4288814,0.0002668862,0.0000360862,0.0001623002,0.00000681275,0.00003564033,0.00002504756],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9740728,"threshold_uncertainty_score":0.999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05193420424889744,"score_gpt":0.3006018289755211,"score_spread":0.2486676247266237,"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."}}