{"id":"W2157007220","doi":"10.1109/icpc.2007.7","title":"A Hybrid Program Model for Object-Oriented Reverse Engineering","year":2007,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Reverse engineering; Granularity; Program comprehension; Scalability; Set (abstract data type); Object-oriented programming; Programming language; Software engineering; Object (grammar); Focus (optics); Domain (mathematical analysis); Unified Modeling Language; Software; Theoretical computer science; Artificial intelligence; Software system; Database","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":[0.001471518,0.0006756075,0.0004897941,0.001286462,0.000601493,0.002293359,0.002002138,0.001731607,0.002514801],"category_scores_gemma":[0.002993827,0.0005339272,0.001287015,0.001271781,0.001932273,0.004077571,0.001986674,0.001756305,0.0008517129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009109357,"about_ca_system_score_gemma":0.001369162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002459339,"about_ca_topic_score_gemma":0.002925825,"domain_scores_codex":[0.998605,0.0004969755,0.00009418261,0.0002062036,0.0005217849,0.0000759072],"domain_scores_gemma":[0.9980797,0.0007357037,0.0001497126,0.0006402196,0.0003207908,0.00007401734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006333721,0.0001353873,0.0009307708,0.0001770472,0.00004143066,0.0004601256,0.001280471,0.1055948,0.0080658,0.8289015,0.001967177,0.0523821],"study_design_scores_gemma":[0.00005423844,0.0001206116,0.0002019997,0.00006184355,0.00005604523,0.0003668436,0.0001612997,0.6076029,0.004579763,0.3439154,0.04283747,0.00004162287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003522324,0.00005453934,0.9932473,0.0001952913,0.000009656392,0.00006938646,0.00005271047,0.000481903,0.002366897],"genre_scores_gemma":[0.109245,0.0002191582,0.8846783,0.0001582302,0.0000225444,0.0005956155,0.0002730154,0.0002643489,0.004543743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002514801,"threshold_uncertainty_score":0.008412898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804730410809013,"score_gpt":0.2830028713124129,"score_spread":0.2649555672043228,"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."}}