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This book constitutes the refereed proceedings of the 5th International School on Engineering Trustworthy Software Systems, SETSS 2019, held in Chongqing, China, in April 2019. The five chapters in this volume provide lectures on leading-edge research in methods and tools for use in computer system engineering. The topics covered in these chapters include Seamless Model-based System Development: Foundations; From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT; Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous…mehr
This book constitutes the refereed proceedings of the 5th International School on Engineering Trustworthy Software Systems, SETSS 2019, held in Chongqing, China, in April 2019. The five chapters in this volume provide lectures on leading-edge research in methods and tools for use in computer system engineering. The topics covered in these chapters include Seamless Model-based System Development: Foundations; From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT; Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous Distributions and Divergence; K - A Semantic Framework for Programming Languages and Formal Analysis Tools; and Software Abstractions and Human-Cyber-Physical Systems Architecture Modelling.
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Autorenporträt
Inhaltsangabe
Seamless Model-based System Development: Foundations.- From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT.- Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous Distributions and Divergence.- K - A Semantic Framework for Programming Languages and Formal Analysis Tools.- Software Abstractions and Human-Cyber-Physical Systems Architecture Modelling.
Seamless Model-based System Development: Foundations.- From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT.- Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous Distributions and Divergence.- K - A Semantic Framework for Programming Languages and Formal Analysis Tools.- Software Abstractions and Human-Cyber-Physical Systems Architecture Modelling.
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