{"id":"W1672898643","doi":"10.1002/smr.1559","title":"Regression test suite selection using dependence analysis","year":2012,"lang":"en","type":"article","venue":"Journal of Software Evolution and Process","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Test suite; Regression testing; Computer science; Suite; Test case; Data mining; Representation (politics); Process (computing); Regression analysis; Machine learning; Software; Software system; 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":[0.0008666534,0.0001186398,0.00021511,0.0004644123,0.0002133491,0.00009544405,0.0002716368,0.00008342952,0.000004795181],"category_scores_gemma":[0.001221674,0.00009254045,0.00008301582,0.00131588,0.00003281682,0.00139634,0.00006036184,0.000210278,0.000001070333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001001602,"about_ca_system_score_gemma":0.0001099705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002314806,"about_ca_topic_score_gemma":0.000001996572,"domain_scores_codex":[0.9988816,0.00005771365,0.0003205231,0.0001420936,0.0003693137,0.0002287137],"domain_scores_gemma":[0.99844,0.0002965952,0.0004801881,0.0001282653,0.0004931474,0.0001618353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007866474,0.00007068388,0.989601,0.00003282799,0.00003988538,0.000002774272,0.0003706337,0.0002475912,0.0001712435,0.00008570749,0.0003453145,0.009024533],"study_design_scores_gemma":[0.0007430617,0.000581054,0.7981454,0.0007891034,0.0007555779,0.003520083,0.00008055542,0.1593345,0.003752318,0.03113183,0.0003363464,0.0008302288],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1274968,0.00142477,0.8702408,0.00004908189,0.0001487208,0.00003481269,6.599993e-7,0.0005950492,0.000009295192],"genre_scores_gemma":[0.8026327,0.00001999239,0.1971586,0.00004350131,0.0001234412,9.324397e-7,2.922681e-7,0.000005062876,0.00001550201],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6751359,"threshold_uncertainty_score":0.377369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402513274456869,"score_gpt":0.308492977013155,"score_spread":0.2844678442685863,"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."}}