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Computer Science Virtual Bookfair

Welcome to the Cambridge University Press College bookfair for Computer Science. We are committed to producing textbooks that will be valuable teaching resources for you, and from which your students will gain a deeper understanding of their subject. On this site you will find details about our textbooks - some already widely adopted, some brand-new, and some that will be launched in the next few months.

The texts are grouped into the following areas:

Introductory Computer Science and Data Structures
Programming Languages, Compilers, and Software Engineering
Algorithms, Theory, and Discrete Mathematics
Scientific and Parallel Computing, Numerical Analysis and Optimization
Bioinformatics
Learning and IR
Graphics, Vision, and Robotics
Networking and Communications
Numerical Recipes

If you are currently teaching in any of these areas, then we are confident you will find texts that will be ideal pedagogic tools for your courses.

Enjoy browsing the site, and thank you for visiting. If we can be of further assistance to you, please contact your sales representative toll free at 1 866 257 3385.

Featured Titles

Mobile Computing Principles

Mobile Computing Principles
Designing and Developing Mobile Applications with UML and XML

  • Reza B'Far, Foreword by Roy T. Fielding

Written to address technical concerns that mobile developers face, this book explores the differences between mobile and stationary applications and the architectural and software development concepts needed to build mobile applications. Reza B'far guides the developer through the development process, using UML from design to implementation. He focuses on general concepts, while using platforms as examples or as possible tools. After introducing UML, XML, and the derivative tools necessary for developing mobile software applications, B'far demonstrates how to build user interfaces for mobile applications.

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Probability and Computing

Probability and Computing
Randomized Algorithms and Probabilistic Analysis

  • Michael Mitzenmacher, Eli Upfal

"This text provides a solid background in probabilistic techniques, illustrating each with well-chosen examples. The explanations are clear, and convey the intuition behind the results and techniques, yet the coverage is rigorous. An excellent advanced undergraduate text."
Peter Bartlett, UC Berkley

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Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms

  • David J. C. MacKay

"...an impressive book, intended as a class text on the subject of the title but having the character and robustness of a focused encyclopedia. The presentation is finely detailed, well documented, and stocked with artistic flourishes."
Mathematical Reviews

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Logic in Computer Science

Logic in Computer Science
Modelling and Reasoning about Systems
2nd Edition

  • Michael Huth, Mark Ryan

"Readers searching for a good book on formal methods will find it here."
Choice

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