The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation. This book takes a lambda calculus approach to organizing computations. It sets out with a brief introduction to lambda calculus, describes a variant of the classical SECD-machine as a basic interpreter for the lambda calculus, and in the main part continues with fully normalizing abstract lambda calculus machines, of which some are interpreting and some execute compiled code.
An all-inclusive survey of the fundamentals of parallel and distributed computing. The use of parallel and distributed computing has increased dramatically over the past few years, giving rise to a variety of projects, implementations, and buzzwords surrounding the subject. Although the areas of parallel and distributed computing have traditionally evolved separately, these models have overlapping goals and characteristics. Parallel and Distributed Computing surveys the models and paradigms in this converging area of parallel and distributed computing and considers the diverse approaches within a common text. Covering a comprehensive set of models and paradigms, the material also skims lightly over more specific details and serves as both an introduction and a survey. Novice readers will be able to quickly grasp a balanced overview with the review of central concepts, problems, and ideas, while the more experienced researcher will appreciate the specific comparisons between models, the coherency of the parallel and distributed computing field, and the discussion of less well-known proposals. Other topics covered include:<br> * Data parallelism<br> * Shared-memory programming<br> * Message passing<br> * Client/server computing<br> * Code mobility<br> * Coordination, object-oriented, high-level, and abstract models<br> * And much more<br> <br> Parallel and Distributed Computing is a perfect tool for students and can be used as a foundation for parallel and distributed computing courses. Application developers will find this book helpful to get an overview before choosing a particular programming style to study in depth, and researchers and programmers will appreciate the wealth of information concerning the various areas of parallel and distributed computing.
Computing Science is a science of constructive methods. The solution of a problem has to be described formally by constructive techniques, if it is to be evaluated on a computer. The Marktoberdorf Advanced Study Institute 1988 presented a comprehensive survey of the recent research in constructive methods in Computing Science. Some approaches to a methodological framework and to supporting tools for specification, development and verification of software systems were discussed in detail. Other lectures dealt with the relevance of the foundations of logic for questions of program construction and with new programming paradigms and formalisms which have proven to be useful for a constructive approach to software development. The construction, specification, design and verification especially of distributed and communicating systems was discussed in a number of complementary lectures. Examples for those approaches were given on several levels such as semaphores, nondeterministic state transition systems with fairness assumptions, decomposition of specifications for concurrent systems in liveness and safety properties and functional specifications of distributed systems. Construction methods in programming that were presented range from type theory, the theory of evidence, theorem provers for proving properties of functional programs to category theory as an abstract and general concept for the description of programming paradigms.
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