{"id":"W2125181275","doi":"10.1109/hpcc.2011.60","title":"Social Network Analysis in Software Testing to Categorize Unit Test Cases Based on Coverage Information","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Test suite; Computer science; Test Management Approach; Regression testing; Test script; Test harness; Reliability engineering; Software quality; Unit testing; Test case; System under test; Software engineering; Software maintenance; Software; Software system; Software construction; Software development; Engineering; Operating system; Machine learning","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":[0.002924031,0.0007794002,0.0008698094,0.0158997,0.001115632,0.001422222,0.0007571035,0.001163825,0.001316114],"category_scores_gemma":[0.02026545,0.0003655585,0.0008410672,0.006658087,0.001034375,0.002691729,0.001045989,0.0006238353,0.0003192009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001272278,"about_ca_system_score_gemma":0.0005241542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005007849,"about_ca_topic_score_gemma":0.005274559,"domain_scores_codex":[0.9960756,0.00209982,0.0002867765,0.0006041289,0.0007806711,0.0001529864],"domain_scores_gemma":[0.9726893,0.02114753,0.002703962,0.001394287,0.001639196,0.0004257075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008226163,0.0007827049,0.2554253,0.001168652,0.001113013,0.0009829367,0.005495908,0.1171887,0.01469386,0.04600797,0.005452982,0.5508654],"study_design_scores_gemma":[0.00004025665,0.0001663805,0.07057127,0.0001458064,0.0002544191,0.0006670577,0.001246775,0.8756443,0.004811758,0.04129814,0.005062116,0.0000916913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4519949,0.001280998,0.5377777,0.0009421118,0.00004758619,0.0005240088,0.001465619,0.0007206929,0.005246386],"genre_scores_gemma":[0.8090305,0.0004243813,0.187138,0.00007826844,0.00007489182,0.0004244044,0.001891994,0.00006697579,0.0008704725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0158997,"threshold_uncertainty_score":0.01546389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04989803146578312,"score_gpt":0.2717220545121415,"score_spread":0.2218240230463584,"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."}}