Discrete Mathematics

For one- or two-term introductory courses in discrete mathematics.

An accessible introduction to the topics of discrete math, this best-selling text also works to expand students’ mathematical maturity.

With nearly 4,500 exercises, Discrete Mathematics provides ample opportunities for students to practice, apply, and demonstrate conceptual understanding. Exercise sets features a large number of applications, especially applications to computer science. The almost 650 worked examples provide ready reference for students as they work. A strong emphasis on the interplay among the various topics serves to reinforce understanding. The text models various problem-solving techniques in detail, then provides opportunity to practice these techniques. The text also builds mathematical maturity by emphasizing how to read and write proofs. Many proofs are illustrated with annotated figures and/or motivated by special Discussion sections. The side margins of the text now include “tiny URLs” that direct students to relevant applications, extensions, and computer programs on the textbook website.

Richard Johnsonbaugh is Professor Emeritus of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago. Prior to his 20-year service at DePaul University, he was a member and sometime chair of the mathematics departments at Morehouse College and Chicago State University. He has a B.A. degree in mathematics from Yale University, M.A. and Ph.D. degrees in mathematics from the University of Oregon, and an M.S. degree in computer science from the University of Illinois, Chicago. His most recent research interests are in pattern recognition, programming languages, algorithms, and discrete mathematics. He is the author or co-author of numerous books and articles in these areas. Several of his books have been translated into various languages. He is a member of the Mathematical Association of America.

1.     Sets and Logic

2.     Proofs

3.     Functions, Sequences, and Relations

4.     Algorithms

5.     Introduction to Number Theory

6.     Counting Methods and the Pigeonhole Principle

7.     Recurrence Relations

8.     Graph Theory

9.     Trees

10.   Network Models

11.   Boolean Algebras and Combinatorial Circuits

12.   Automata, Grammars, and Languages

13.   Computational Geometry

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