{"id":"W4200053401","doi":"10.1109/models-c53483.2021.00095","title":"MRegTest: A Replay-Based Regression Testing Tool for Distributed UML-RT Models","year":2021,"lang":"en","type":"article","venue":"2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Regression testing; Semantics (computer science); Model-based testing; Process (computing); Set (abstract data type); Unified Modeling Language; Timestamp; Regression analysis; Data mining; Test case; Programming language; Machine learning; Real-time computing; Software; Software system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002288193,0.001754026,0.0007135029,0.001760057,0.000323484,0.0008919278,0.002418169,0.001205919,0.007049445],"category_scores_gemma":[0.01050503,0.0008040687,0.001318133,0.0005063883,0.0006622472,0.002012942,0.001416292,0.001435095,0.001779509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005269716,"about_ca_system_score_gemma":0.0009356377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960542,"about_ca_topic_score_gemma":0.00304115,"domain_scores_codex":[0.9980341,0.0005879599,0.0001739412,0.0003650176,0.0007251702,0.0001139073],"domain_scores_gemma":[0.9938787,0.00393508,0.0006657084,0.0008990961,0.0005255392,0.00009591081],"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":[0.001181711,0.0008453223,0.01860639,0.00207218,0.0004892389,0.003139584,0.001922533,0.2511744,0.08310943,0.0249257,0.05871023,0.5538232],"study_design_scores_gemma":[0.0002092291,0.0003652443,0.003112219,0.0002583741,0.0001187476,0.001180345,0.0001750325,0.8747118,0.06701407,0.01070557,0.04201209,0.0001373141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02381095,0.0002232533,0.7789251,0.0001909494,0.00006149276,0.0001620726,0.001263933,0.1932229,0.002139346],"genre_scores_gemma":[0.3543339,0.0003865359,0.611622,0.0002725789,0.00004086503,0.0006660009,0.004840901,0.02285227,0.004984981],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007049445,"threshold_uncertainty_score":0.02358276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1117479861438778,"score_gpt":0.3226693981312517,"score_spread":0.210921411987374,"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."}}