{"id":"W2139599608","doi":"10.22215/etd/2004-05823","title":"Performance stress testing of real-time systems using genetic algorithms","year":2004,"lang":"en","type":"dissertation","venue":"","topic":"Real-Time Systems Scheduling","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Stress testing (software); Task (project management); Unit testing; Integration testing; Real-time computing; White-box testing; Test strategy; Execution time; Reliability engineering; Distributed computing; Engineering; Operating system; Software system; Software; Systems engineering","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":[0.001725554,0.0008289113,0.0004287965,0.001023721,0.0002942653,0.0007675955,0.0008292351,0.0007302281,0.0006120822],"category_scores_gemma":[0.009171802,0.0003113345,0.0006267751,0.0006019229,0.001032273,0.000683432,0.0004330229,0.0006103028,0.00007880631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008016561,"about_ca_system_score_gemma":0.00101507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003141268,"about_ca_topic_score_gemma":0.001908639,"domain_scores_codex":[0.9985161,0.0008013326,0.00006283187,0.0001382396,0.0003821646,0.00009919896],"domain_scores_gemma":[0.9930428,0.00556758,0.0005635187,0.0002863971,0.00045912,0.00008060547],"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":[0.00009181256,0.0001440079,0.003106117,0.00008294526,0.00005916005,0.000135641,0.0001435075,0.9071698,0.01076299,0.009832233,0.0002303703,0.06824144],"study_design_scores_gemma":[0.00001808593,0.00007366933,0.0004376029,0.00001486604,0.00001319452,0.00003160927,0.00001913351,0.9868216,0.005930369,0.006323893,0.0003077238,0.000008264848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1638199,0.0002723312,0.8322999,0.0002268591,0.00002009618,0.00009079408,0.00003608764,0.0007241232,0.00250988],"genre_scores_gemma":[0.7046475,0.0002303557,0.2939698,0.00006639567,0.00001234256,0.0001524562,0.0001134959,0.00007317676,0.0007343045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003141268,"threshold_uncertainty_score":0.00912571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02511738896510806,"score_gpt":0.2636065452689292,"score_spread":0.2384891563038211,"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."}}