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Discrete Mathematics and its Applications is a focused introduction to the primary themes in a discrete mathematics course, as introduced through extensive applications, expansive discussion, and detailed exercise sets. These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.

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• Discrete Mathematics and Its Applications, Fifth Edition
• 1 The Foundations: Logic and Proof, Sets, and Functions
• 1.1 Logic
• 1.2 Propositional Equivalences
• 1.3 Predicates and Quantifiers
• 1.4 Nested Quantifiers
• 1.5 Methods of Proof
• 1.6 Sets
• 1.7 Set Operations
• 1.8 Functions
• 2 The Fundamentals: Algorithms, the Integers, and Matrices
• 2.1 Algorithms
• 2.2 The Growth of Functions
• 2.3 Complexity of Algorithms
• 2.4 The Integers and Division
• 2.5 Applications of Number Theory
• 2.6 Matrices
• 3 Mathematical Reasoning, Induction, and Recursion
• 3.1 Proof Strategy
• 3.2 Sequences and Summations
• 3.3 Mathematical Induction
• 3.4 Recursive Definitions and Structural Induction
• 3.5 Recursive Algorithms
• 3.6 Program Correctness
• 4 Counting
• 4.1 The Basics of Counting
• 4.2 The Pigeonhole Principle
• 4.3 Permutations and Combinations
• 4.4 Binomial Coefficients
• 4.5 Generalized Permutations and Combinations
• 4.6 Generating Permutations and Combinations
• 5 Discrete Probability
• 5.1 An Introduction to Discrete Probability
• 5.2 Probability Theory
• 5.3 Expected Value and Variance
• 6 Advanced Counting Techniques
• 6.1 Recurrence Relations
• 6.2 Solving Recurrence Relations
• 6.3 Divide-and-Conquer Algorithms and Recurrence Relations
• 6.4 Generating Functions
• 6.5 Inclusion-Exclusion
• 6.6 Applications of Inclusion-Exclusion
• 7 Relations
• 7.1 Relations and Their Properties
• 7.2 n-ary Relations and Their Applications
• 7.3 Representing Relations
• 7.4 Closures of Relations
• 7.5 Equivalence Relations
• 7.6 Partial Orderings
• 8 Graphs
• 8.1 Introduction to Graphs
• 8.2 Graph Terminology
• 8.3 Representing Graphs and Graph Isomorphism
• 8.4 Connectivity
• 8.5 Euler and Hamilton Paths
• 8.6 Shortest-Path Problems
• 8.7 Planar Graphs
• 8.8 Graph Coloring
• 9 Trees
• 9.1 Introduction to Trees
• 9.2 Applications of Trees
• 9.3 Tree Traversal
• 9.4 Spanning Trees
• 9.5 Minimum Spanning Trees
• 10 Boolean Algebra
• 10.1 Boolean Functions
• 10.2 Representing Boolean Functions
• 10.3 Logic Gates
• 10.4 Minimization of Circuits
• 11 Modeling Computation
• 11.1 Languages and Grammars
• 11.2 Finite-State Machines with Output
• 11.3 Finite-State Machines with No Output
• 11.4 Language Recognition
• 11.5 Turing Machines
• Appendixes
• A.1 Exponential and Logarithmic Functions
• A.2 Pseudocode