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Record Nr. |
UNINA9910413437403321 |
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Titolo |
Engineering Trustworthy Software Systems : 5th International School, SETSS 2019, Chongqing, China, April 21–27, 2019, Tutorial Lectures / / edited by Jonathan P. Bowen, Zhiming Liu, Zili Zhang |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XVII, 221 p. 32 illus.) |
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Collana |
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Programming and Software Engineering ; ; 12154 |
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Disciplina |
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Soggetti |
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Software engineering |
Computer communication systems |
Artificial intelligence |
Computer programming |
Architecture, Computer |
Natural language processing (Computer science) |
Software Engineering/Programming and Operating Systems |
Computer Communication Networks |
Artificial Intelligence |
Programming Techniques |
Computer System Implementation |
Natural Language Processing (NLP) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 5th International School on Engineering Trustworthy Software Systems, SETSS 2019, held |
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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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