Safety Assurance under Uncertainties: From Software to Cyber-Physical/Machine Learning Systems
Giới thiệu về sách điện tử này
The book is the first to provide a comprehensive overview of such united and interdisciplinary efforts. Driven by automated driving systems as a leading example, the book describes diverse techniques to specify, model, test, analyze, and verify modern software systems. Coming out of a collaboration between industry and basic academic research, the book covers both practical analysis techniques (readily applicable to existing systems) and more long-range design techniques (that call for new designs but bring a greater degree of assurance).
The book provides high-level intuitions and use-cases of each technique, rather than technical details, with plenty of pointers for interested readers.
Giới thiệu tác giả
Ichiro Hasuo, Ph.D. (cum laude, Radboud University Nijmegen, 2008), is a Professor at National Institute of Informatics (NII), Tokyo, Japan. He is at the same time the Research Director of the JST ERATO "Metamathematics for Systems Design'' Project, and the Director of Research Center for Mathematical Trust in Software and Systems at NII. His research field is software science and his interests include formal verification, mathematical and logical structures, category theory, integration of formal methods and testing, and application to cyber-physical systems and systems with statistical machine learning components.
Fuyuki Ishikawa, Ph.D. (The University of Tokyo, 2007), is an Associate Professor in Information Systems Architecture Science Research Division and the Director of GRACE Center, at National Institute of Informatics (NII), Tokyo, Japan. His research focuses on software engineering, especially for dependability of emerging AI and smart cyber-physical systems, including test generation, fault analysis, automated repair, and formal verification for automated driving systems. He is leading relevant initiatives of the Japanese industry such as the QA4AI guidelines for quality assurance of AI systems.
