{"id":"W2097186696","doi":"10.1109/icst.2008.57","title":"An Empirical Study on Bayesian Network-based Approach for Test Case Prioritization","year":2008,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Regression testing; Bayesian network; Java; Test case; Data mining; Software bug; Machine learning; Bayesian probability; Prioritization; Empirical research; Test (biology); Software; Artificial intelligence; Regression analysis; Software system; Engineering; Software construction","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":[],"consensus_categories":[],"category_scores_codex":[0.0003729679,0.0001149183,0.0001143333,0.0001015482,0.0002169336,0.00008593388,0.0004310785,0.00004947366,0.000003484656],"category_scores_gemma":[0.0003528448,0.000102156,0.00003195841,0.0005543513,0.00002045353,0.0001756483,0.000043664,0.0001148947,0.000004961726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005452482,"about_ca_system_score_gemma":0.00009720399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001477989,"about_ca_topic_score_gemma":0.000004389037,"domain_scores_codex":[0.9987345,0.00005847964,0.000142796,0.0004292294,0.0003108984,0.0003240959],"domain_scores_gemma":[0.9981171,0.0009957476,0.00001752614,0.0006154163,0.000100637,0.000153588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001772475,0.002728384,0.7933302,0.00002027082,0.00001287385,0.0008942068,0.0007734757,0.1926617,0.00001874514,0.0003396453,0.004953365,0.004249431],"study_design_scores_gemma":[0.0005774897,0.001244719,0.05363151,0.000002221653,0.000001911201,0.000152942,0.00002155574,0.9440634,0.00007214516,0.00001874838,0.00006916452,0.0001441445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0776874,0.000004179705,0.9208667,0.00007861306,0.00006595982,0.0007015161,0.000001119609,0.0004980576,0.00009643613],"genre_scores_gemma":[0.7761016,1.163004e-7,0.2234995,0.0001125033,0.0001202576,0.00009345693,0.00000522338,0.00001349202,0.00005380323],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7514017,"threshold_uncertainty_score":0.4165801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057616437589533,"score_gpt":0.3312695450053025,"score_spread":0.2806933806294071,"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."}}