{"id":"W2006253492","doi":"10.1016/j.jss.2007.05.037","title":"Traffic-aware stress testing of distributed real-time systems based on UML models using genetic algorithms","year":2007,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of Calgary","funders":"","keywords":"Computer science; Unified Modeling Language; Real-time computing; Test case; Focus (optics); Sequence diagram; Scenario testing; Algorithm; Stress test; Distributed computing; Artificial intelligence; Machine learning; Software; Variety (cybernetics)","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":[0.0009886987,0.0008205864,0.0006643391,0.001126677,0.0003739562,0.0007981312,0.001101007,0.0008062203,0.0007943844],"category_scores_gemma":[0.005626062,0.0003557932,0.000663427,0.0003919429,0.0005984919,0.00107208,0.0004937393,0.0004739964,0.00006945836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133277,"about_ca_system_score_gemma":0.001010695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0074474,"about_ca_topic_score_gemma":0.006252517,"domain_scores_codex":[0.9992929,0.0003282509,0.00002872194,0.0000887116,0.0001817609,0.00007962968],"domain_scores_gemma":[0.994311,0.004226698,0.0005018054,0.0002975632,0.0005453008,0.0001176917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001826701,0.0001325346,0.003236843,0.00004316571,0.00005290166,0.0000921024,0.0001137407,0.9544748,0.007009468,0.003584252,0.0001760864,0.03090157],"study_design_scores_gemma":[0.000009068759,0.00001672441,0.0001468807,0.000003002817,0.00001064183,0.000007441363,0.00000650197,0.9975463,0.001224876,0.0009962379,0.00003011324,0.000002205355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.532086,0.0001760833,0.4632936,0.0002226203,0.00003167966,0.00006273134,0.00004798339,0.002078778,0.002000598],"genre_scores_gemma":[0.9615555,0.00002655604,0.03805238,0.00001534545,0.000003850662,0.00002602921,0.00003247922,0.00004385493,0.0002440397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0074474,"threshold_uncertainty_score":0.01480806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03951929322770974,"score_gpt":0.2682844576664398,"score_spread":0.22876516443873,"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."}}