{"id":"W2925127136","doi":"10.1007/s11219-018-9437-3","title":"Testing self-healing cyber-physical systems under uncertainty: a fragility-oriented approach","year":2019,"lang":"en","type":"article","venue":"Software Quality Journal","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Horizon 2020 Framework Programme; Norges Forskningsråd","keywords":"Fragility; Reliability engineering; Normality; Computer science; Reliability (semiconductor); Cyber-physical system; Data mining; Engineering; Mathematics; Statistics","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":[0.004773534,0.001264822,0.0012674,0.002246971,0.0007685533,0.001775484,0.002545136,0.001583158,0.001532416],"category_scores_gemma":[0.01935368,0.0005434034,0.001397415,0.0009732832,0.003906408,0.003188129,0.00255417,0.001810398,0.0001215453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243334,"about_ca_system_score_gemma":0.001466286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00252106,"about_ca_topic_score_gemma":0.001784746,"domain_scores_codex":[0.9965875,0.001480733,0.0001391976,0.0003861834,0.001086779,0.0003195131],"domain_scores_gemma":[0.9823162,0.01386492,0.001299402,0.001153177,0.001079483,0.0002869],"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":[0.0001620747,0.0001432604,0.003097958,0.0002655426,0.0001823525,0.0004249565,0.0004655585,0.7956812,0.004424917,0.1374173,0.0005781517,0.05715679],"study_design_scores_gemma":[0.00001250699,0.00007731205,0.0002685506,0.00003286812,0.00004019635,0.00007704707,0.00009407955,0.9163173,0.001612045,0.08112196,0.0003322714,0.00001390498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0305355,0.0002591953,0.9653995,0.0007159987,0.00003153224,0.00008192324,0.00003354599,0.0002887724,0.002654103],"genre_scores_gemma":[0.8562109,0.0003449296,0.1415625,0.0002353281,0.00008299107,0.0001349598,0.00005980906,0.0000936826,0.001274788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004773534,"threshold_uncertainty_score":0.02524513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04131213216160864,"score_gpt":0.308153895772097,"score_spread":0.2668417636104884,"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."}}