In Chapter 2, Sorting Algorithms and Fundamental Data Structures, we introduced, among other sorting algorithms, merge and quick sort. A peculiarity of both algorithms is that they divide the problem into subproblems that are smaller instances of the same, solve each one of the subproblems recursively, and then combine the solutions to the subproblems into the solution for the original problem. This strategy forms the basis of the divide and conquer paradigm.
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Beginning Java Data Structures and Algorithms
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Beginning Java Data Structures and Algorithms
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Overview of this book
Learning about data structures and algorithms gives you a better insight on how to solve common programming problems. Most of the problems faced everyday by programmers have been solved, tried, and tested. By knowing how these solutions work, you can ensure that you choose the right tool when you face these problems.
This book teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications.
Table of Contents (8 chapters)
Preface
Free Chapter
Algorithms and Complexities
Sorting Algorithms and Fundamental Data Structures
Hash Tables and Binary Search Trees
Algorithm Design Paradigms
String Matching Algorithms
Graphs, Prime Numbers, and Complexity Classes
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