{"id":"W2584970301","doi":"10.1109/icosst.2016.7838329","title":"Safe regression test suite optimization: A review","year":2016,"lang":"en","type":"review","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Test suite; Regression testing; Computer science; Suite; Reduction (mathematics); Test case; Fuzzy logic; Machine learning; Artificial intelligence; Regression analysis; Mathematics; Software","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":[0.002478387,0.001547445,0.00191996,0.004734246,0.0002758924,0.001054496,0.003023524,0.001434862,0.002800502],"category_scores_gemma":[0.007053512,0.0007314867,0.001210146,0.005501502,0.000671858,0.001662801,0.0007142363,0.001017336,0.001362287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009145928,"about_ca_system_score_gemma":0.002318589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002881747,"about_ca_topic_score_gemma":0.002972194,"domain_scores_codex":[0.9983423,0.0002923057,0.0002804596,0.00024561,0.0007765644,0.00006271403],"domain_scores_gemma":[0.9931484,0.004512825,0.0006193818,0.000205544,0.001384049,0.0001298258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004462378,0.00009319529,0.0005059135,0.01758708,0.0001300932,0.0001185997,0.00004543648,0.002571384,0.0008998942,0.002555431,0.01053888,0.9649096],"study_design_scores_gemma":[0.00007371277,0.0006811276,0.003746599,0.02279679,0.0008320468,0.003276814,0.0001744077,0.005198922,0.004882771,0.007979947,0.9502207,0.000136111],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004999728,0.99424,0.003393311,0.0002762931,0.0001099025,0.00003318999,0.00005374653,0.00005394372,0.001339659],"genre_scores_gemma":[0.005530185,0.9864118,0.006640108,0.0002242074,0.000173259,0.00005982352,0.0002390858,0.00003488397,0.0006865744],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004734246,"threshold_uncertainty_score":0.01310712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05784089282187099,"score_gpt":0.3639114011909279,"score_spread":0.3060705083690569,"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."}}