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The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it.
This book presents the revised final versions of eight lectures given by leading researchers at the First Summer School on Theoretical Aspects of Computer Science in Tehran, Iran, in July 2000. The lectures presented are devoted to quantum computation, approximation algorithms, self-testing/correction, algebraic modeling of data, the regularity lemma, multiple access communication and combinatorial designs, graph-theoretical methods in computer vision, and low-density parity-check codes.
Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading
This first part presents chapters on models of computation, complexity theory, data structures, and efficient computation in many recognized sub-disciplines of Theoretical Computer Science.
The book is addressed to young people interested in computer technologies and computer science. The objective of this book is to provide the reader with all the necessary elements to get him or her started in the modern field of informatics and to allow him or her to become aware of the relationship between key areas of computer science. The book is addressed not only to future software developers, but also to all who are interested in computing in a widely understood sense. The authors also expect that some computer professionals will want to review this book to lift themselves above the daily grind and to embrace the excellence of the whole field of computer science. Unlike existing books, this one bypasses issues concerning the construction of computers and focuses only on information processing. Recognizing the importance of the human factor in information processing, the authors intend to present the theoretical foundations of computer science, software development rules, and some business aspects of informatics in non-technocratic, humanistic terms.
"Of all the books I have covered in the Forum to date, this set is the most unique and possibly the most useful to the SIGACT community, in support both of teaching and research.... The books can be used by anyone wanting simply to gain an understanding of one of these areas, or by someone desiring to be in research in a topic, or by instructors wishing to find timely information on a subject they are teaching outside their major areas of expertise." -- Rocky Ross, "SIGACT News" "This is a reference which has a place in every computer science library." -- Raymond Lauzzana, "Languages of Design" The Handbook of Theoretical Computer Science provides professionals and students with a comprehensive overview of the main results and developments in this rapidly evolving field. Volume A covers models of computation, complexity theory, data structures, and efficient computation in many recognized subdisciplines of theoretical computer science. Volume B takes up the theory of automata and rewriting systems, the foundations of modern programming languages, and logics for program specification and verification, and presents several studies on the theoretic modeling of advanced information processing. The two volumes contain thirty-seven chapters, with extensive chapter references and individual tables of contents for each chapter. There are 5,387 entry subject indexes that include notational symbols, and a list of contributors and affiliations in each volume.
"This book provides a comprehensive understanding and coverage of the various theories, models and related research approaches used within IS research"--Provided by publisher.
Theoretical Studies in Computer Science focuses on the field of theoretical computer science. This book discusses the context-free multi-languages, non-membership in certain families of context-free languages, and single tree grammars. The complexity of structural containment and equivalence, interface between language theory and database theory, and automata theory for database theoreticians are also deliberated. This text likewise covers the datalog linearization of chain queries, expressive power of query languages, and object identity and query equivalences. Other topics include the unified approach to data and meta-data modification for data/knowledge bases, polygon clipping algorithms, and convex polygon generator. This publication is intended for computer scientists and researchers interested in theoretical computer science.
Set theory can be considered a unifying theory for mathematics. This book covers the fundamentals of the subject.
This text strikes a good balance between rigor and an intuitive approach to computer theory. Covers all the topics needed by computer scientists with a sometimes humorous approach that reviewers found "refreshing". It is easy to read and the coverage of mathematics is fairly simple so readers do not have to worry about proving theorems.