{"id":"W2145149095","doi":"10.1002/stvr.461","title":"Regression test suite prioritization using system models","year":2011,"lang":"en","type":"article","venue":"Software Testing Verification and Reliability","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Regression testing; Test suite; Computer science; Prioritization; Reliability engineering; Test (biology); Test case; Fault detection and isolation; System under test; Test Management Approach; Empirical research; Overhead (engineering); Suite; Regression analysis; Data mining; Machine learning; Artificial intelligence; Engineering; Software system; Statistics; Software; 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":[],"consensus_categories":[],"category_scores_codex":[0.000945633,0.0002061799,0.000204353,0.0001113609,0.0004111127,0.0001146786,0.0004239031,0.0001428814,0.000001401075],"category_scores_gemma":[0.004143094,0.0001795158,0.00003872257,0.0006035186,0.0001172455,0.0005927942,0.0001847756,0.000172393,0.000004381627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000129563,"about_ca_system_score_gemma":0.0001056944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003525542,"about_ca_topic_score_gemma":6.31341e-7,"domain_scores_codex":[0.9982753,0.0001222026,0.0004146462,0.0006757239,0.0002511869,0.0002608725],"domain_scores_gemma":[0.9973971,0.000752153,0.0002705092,0.0009540851,0.0004930947,0.0001330091],"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":[0.00002658283,0.0005799589,0.8201281,0.001187835,0.00001416362,0.0000246051,0.004711619,0.0007955329,0.001894717,0.0130309,0.0009083586,0.1566976],"study_design_scores_gemma":[0.0002253526,0.0001320338,0.07373703,0.0006393236,0.00002227429,0.0001258418,0.00002902492,0.8645381,0.00108283,0.05896768,0.00003419626,0.0004662886],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0458025,0.0001063468,0.9375282,0.00002780739,0.0001878699,0.0003104212,0.000004116292,0.01548681,0.0005459447],"genre_scores_gemma":[0.5132034,0.000003265862,0.4867109,0.00002299783,0.00001998205,0.00001324352,0.000002727683,0.00001104981,0.00001240656],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8637426,"threshold_uncertainty_score":0.732044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08413484429999112,"score_gpt":0.2648815431189903,"score_spread":0.1807466988189992,"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."}}