{"id":"W4312834255","doi":"10.1109/tse.2022.3213041","title":"Data-Driven Mutation Analysis for Cyber-Physical Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission; European Space Agency","keywords":"Computer science; Interoperability; Test suite; Set (abstract data type); Data mining; Suite; Mutation; Software; Quality (philosophy); Programming language; Software engineering; Theoretical computer science; Test case; Machine learning; World Wide Web","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":[0.001878582,0.001152268,0.0007680199,0.003723452,0.0004882949,0.001255272,0.001282984,0.000888247,0.001270576],"category_scores_gemma":[0.009719999,0.0003394663,0.00168139,0.0009881011,0.001455111,0.001215081,0.001110248,0.001311142,0.0002558086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001470844,"about_ca_system_score_gemma":0.001698836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004151579,"about_ca_topic_score_gemma":0.002488908,"domain_scores_codex":[0.997514,0.000590904,0.0001486929,0.0003800354,0.001215076,0.0001514141],"domain_scores_gemma":[0.9933924,0.004318061,0.0006096191,0.000463956,0.001068842,0.0001470476],"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":[0.0002153358,0.0002492368,0.008937936,0.0003176238,0.0001624367,0.0009263052,0.0002395751,0.733138,0.04398169,0.06180968,0.001769196,0.1482529],"study_design_scores_gemma":[0.00001668637,0.00004429942,0.0005051692,0.00001378427,0.0000154535,0.00009733525,0.00001650541,0.9732617,0.0124655,0.01277164,0.0007725784,0.00001945539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05583683,0.000193438,0.9387795,0.0002169963,0.0000433297,0.0001064974,0.0002683301,0.003181292,0.001373741],"genre_scores_gemma":[0.6022233,0.000239852,0.3943647,0.0001751943,0.00003158809,0.0002962909,0.0008649233,0.000398994,0.001405177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004151579,"threshold_uncertainty_score":0.01067179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03462965960977726,"score_gpt":0.2702867977014546,"score_spread":0.2356571380916774,"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."}}