Algorithm Design and Applications

Introducing a NEW addition to our growing library of computer science titles, Algorithm Design and Applications, by Michael T. Goodrich & Roberto Tamassia! Algorithms is a course required for all computer science majors, with a strong focus on theoretical topics. Students enter the course after gaining hands-on experience with computers, and are expected to learn how algorithms can be applied to a variety of contexts. This new book integrates application with theory.

Goodrich & Tamassia believe that the best way to teach algorithmic topics is to present them in a context that is motivated from applications to uses in society, computer games, computing industry, science, engineering, and the internet. The text teaches students about designing and using algorithms, illustrating connections between topics being taught and their potential applications, increasing engagement.

Table of Contents

Chapter 1 Algorithm Analysis

Part I Data Structures
Chapter 2 Basic Data Structures
Chapter 3 Binary Search Trees
Chapter 4 Balanced Binary Search Trees
Chapter 5 Priority Queues and Heaps
Chapter 6 Hash Tables
Chapter 7 Union-Find Structures

Part II Sorting and Selection
Chapter 8 Merge-Sort and Quick-Sort
Chapter 9 Fast Sorting and Selection

Part III Fundamental Techniques
Chapter 10 The Greedy Method
Chapter 11 Divide-and-Conquer
Chapter 12 Dynamic Programming
Chapter 13 Graphs and Traversals

Part IV Graph Algorithms
Chapter 14 Shortest Paths
Chapter 15 Minimum Spanning Trees
Chapter 16 Network Flow and Matching

Part V Computational Intractability
Chapter 17 NP-Completeness
Chapter 18 Approximation Algorithms

Part VI Additional Topics
Chapter 19 Randomized Algorithms
Chapter 20 B-Trees and External Memory
Chapter 21 Multidimensional Searching
Chapter 22 Computational Geometry
Chapter 23 String Algorithms
Chapter 24 Cryptography
Chapter 25 The Fast Fourier Transform
Chapter 26 Linear Programming