{"id":"W4378675137","doi":"10.1016/j.jss.2023.111755","title":"On the maintenance support for microservice-based systems through the specification and the detection of microservice antipatterns","year":2023,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; École de Technologie Supérieure; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Microservices; Software engineering; Computer science; Software; Software development; Operating 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002891588,0.0001464051,0.0003463726,0.00006126263,0.0004114264,0.0002518436,0.0006216555,0.00008051506,5.431856e-7],"category_scores_gemma":[0.0001427386,0.00005996217,0.0001290599,0.0003496065,0.0001433543,0.000250836,0.00006650666,0.0001805466,0.000003452574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003593891,"about_ca_system_score_gemma":0.0000667597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002397308,"about_ca_topic_score_gemma":0.00001361515,"domain_scores_codex":[0.9983265,0.0002303621,0.000704298,0.0001963275,0.0003401476,0.0002023],"domain_scores_gemma":[0.9965904,0.001483762,0.0008529095,0.0005323268,0.0005047094,0.00003593076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01091488,0.001658075,0.2846427,0.06859799,0.00411104,0.0001705652,0.1929816,0.05695386,0.08032974,0.1430683,0.07222028,0.08435097],"study_design_scores_gemma":[0.03122822,0.00557542,0.3817876,0.01441673,0.0007138894,0.003995694,0.04566475,0.2955473,0.01879564,0.0128589,0.1869024,0.002513506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5793465,0.002172942,0.4106098,0.003895143,0.00244899,0.001416805,0.00003540977,0.00005845138,0.0000160563],"genre_scores_gemma":[0.9990168,0.0002177984,0.0001680025,0.0002590009,0.0001922184,0.00005099535,0.000001248336,0.00001089629,0.0000831067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4196703,"threshold_uncertainty_score":0.3164401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045165233466532,"score_gpt":0.2449363396603856,"score_spread":0.2244846873257202,"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."}}