{"id":"W4378676770","doi":"10.1109/icstw58534.2023.00060","title":"Analysis of mutation operators for FSM testing","year":2023,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mutation testing; Mutation; Computer science; Operator (biology); Finite-state machine; Software testing; Software fault tolerance; Process (computing); Software; Set (abstract data type); Fault (geology); Mutant; Theoretical computer science; Algorithm; Programming language; Artificial intelligence; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003513517,0.0000423304,0.0001029226,0.0003702132,0.00004919562,0.00003430527,0.0002356382,0.00001941171,0.000001459786],"category_scores_gemma":[0.001069541,0.00003671542,0.00005062685,0.00314763,0.000009519659,0.00009450192,0.00006132293,0.0000169225,0.000003434625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007425838,"about_ca_system_score_gemma":0.00002196122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008486558,"about_ca_topic_score_gemma":0.000003553611,"domain_scores_codex":[0.9995173,0.00001146386,0.0001311127,0.0001500957,0.00009154974,0.00009851598],"domain_scores_gemma":[0.998755,0.0008225112,0.00004604632,0.0002144465,0.0001422057,0.00001982198],"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":[0.000003717096,0.00007311844,0.232014,0.00006417507,0.0004798684,0.00001410625,0.001882566,0.01316358,0.002162682,0.04411873,0.03164942,0.6743741],"study_design_scores_gemma":[0.00003896922,0.00004313627,0.01573743,0.000007207806,0.00003639058,6.329728e-7,0.000004450865,0.9685295,0.002905914,0.01261665,0.00002357571,0.00005616716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03578383,0.000003507975,0.9551799,0.00009413682,0.00003842194,0.00007108802,0.00000150858,0.008486767,0.0003407867],"genre_scores_gemma":[0.552801,1.250801e-7,0.4470686,0.00004556632,0.00000533665,0.0000144639,0.000003670843,0.000002275004,0.00005899871],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9553659,"threshold_uncertainty_score":0.1512332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06239286997447335,"score_gpt":0.3228523354153964,"score_spread":0.2604594654409231,"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."}}