Mathematics plays a key role in computer science, some researchers would consider computers as nothing but the physical embodiment of mathematical systems. And whether you are designing a digital circuit, a computer program or a new programming language, you need mathematics to be able to reason about the design -- its correctness, robustness and dependability. This book covers the foundational mathematics necessary for courses in computer science. The common approach to presenting mathematical concepts and operators is to define them in terms of properties they satisfy, and then based on these definitions develop ways of computing the result of applying the operators and prove them correct. This book is mainly written for computer science students, so here the author takes a different approach: he starts by defining ways of calculating the results of applying the operators and then proves that they satisfy various properties. After justifying his underlying approach the author offers detailed chapters covering propositional logic, predicate calculus, sets, relations, discrete structures, structured types, numbers, and reasoning about programs. The book contains chapter and section summaries, detailed proofs and many end-of-section exercises -- key to the learning process. The book is suitable for undergraduate and graduate students, and although the treatment focuses on areas with frequent applications in computer science, the book is also suitable for students of mathematics and engineering.

This book provides a hands-on introduction to runtime verification which guides the reader from zero to sufficient practical knowledge required to consider and apply it in industry. It starts with almost no assumptions on the knowledge of the reader and provides exercises throughout the book through which the reader builds their own runtime verification tool. All that is required are basic programming skills and a good working knowledge of the object-oriented paradigm, ideally Java. Drawing from years of the authors' real-world experience, the reader progresses from manually writing runtime verification code to instrumenting monitoring using aspect-oriented programming, after which they explore increasing levels of specification abstraction: automata, regular expressions, and linear time temporal logic. A range of other topics is also explored in the book, including real-time properties, concerns of efficiency and persistence, integration with testing and architectural considerations. The book is written for graduate students specializing in software engineering as well as for industry professionals who need an introduction to the topic of runtime verification. While the book focuses on underlying foundations and practical techniques, it additionally provides for each chapter a reading list in the appendix for the interested reader who would like to deepen their knowledge in a particular area.

This book constitutes the refereed proceedings of the 5th International Workshop on Controlled Natural Language, CNL 2016, held in Aberdeen, UK, in July 2016. The 11 full papers presented were carefully reviewed and selected from 15 submissions. The topics range from natural languages which are controlled, to controlled languages with a natural language flavour; and from more theoretical results to interfaces, reasoning engines and real-life applications of CNLs.

Mathematics plays a key role in computer science, some researchers would consider computers as nothing but the physical embodiment of mathematical systems. And whether you are designing a digital circuit, a computer program or a new programming language, you need mathematics to be able to reason about the design -- its correctness, robustness and dependability. This book covers the foundational mathematics necessary for courses in computer science. The common approach to presenting mathematical concepts and operators is to define them in terms of properties they satisfy, and then based on these definitions develop ways of computing the result of applying the operators and prove them correct. This book is mainly written for computer science students, so here the author takes a different approach: he starts by defining ways of calculating the results of applying the operators and then proves that they satisfy various properties. After justifying his underlying approach the author offers detailed chapters covering propositional logic, predicate calculus, sets, relations, discrete structures, structured types, numbers, and reasoning about programs. The book contains chapter and section summaries, detailed proofs and many end-of-section exercises -- key to the learning process. The book is suitable for undergraduate and graduate students, and although the treatment focuses on areas with frequent applications in computer science, the book is also suitable for students of mathematics and engineering.