Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C#

Description

A more intuitive approach to the mathematical foundation of computer science Discrete mathematics is the basis of much of computer science, from algorithms and automata theory to combinatorics and graph theory. This textbook covers the discrete mathematics that every computer science student needs to learn. Guiding students quickly through thirty-one short chapters that discuss one major topic each, this flexible book can be tailored to fit the syllabi for a variety of courses. Proven in the classroom, Essential Discrete Mathematics for Computer Science aims to teach mathematical reasoning as well as concepts and skills by stressing the art of proof. It is fully illustrated in color, and each chapter includes a concise summary as well as a set of exercises. The text requires only precalculus, and where calculus is needed, a quick summary of the basic facts is provided. Essential Discrete Mathematics for Computer Science is the ideal introductory textbook for standard undergraduate courses, and is also suitable for high school courses, distance education for adult learners, and self-study. The essential introduction to discrete mathematics Features thirty-one short chapters, each suitable for a single class lesson Includes more than 300 exercises Almost every formula and theorem proved in full Breadth of content makes the book adaptable to a variety of courses Each chapter includes a concise summary Solutions manual available to instructors Cover Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C# Copyright Dedication About the Author About the Technical Editor Credits Acknowledgments Contents at a glance Contents Introduction 1 Algorithm Basics 2 Numerical Algorithms 3 Linked Lists 4 Arrays 5 Stacks and Queues 6 Sorting 7 Searching 8 Hash Tables 9 Recursion 10 Trees 11 Balanced Trees 12 Decision Trees 13 Basic Network Algorithms 14 More Network Algorithms 15 String Algorithms 16 Cryptography 17 Complexity Theory 18 Distributed Algorithms 19 Interview Puzzles APPENDIX A. Summary of Algorithmic Concepts APPENDIX B. Solutions to Exercises Glossary Index