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Beginning Java Data Structures and Algorithms

Beginning Java Data Structures and Algorithms

By : James Cutajar
4.6 (10)
Buy this Book
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Beginning Java Data Structures and Algorithms

Beginning Java Data Structures and Algorithms

4.6 (10)
By: James Cutajar
Buy this Book

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)
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Preface
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Preface
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Who This Book Is For
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What This Book Covers
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1
Algorithms and Complexities
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Algorithms and Complexities
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Developing Our First Algorithm
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Measuring Algorithmic Complexity with Big O Notation
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Identifying Algorithms with Different Complexities
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Summary
2
Sorting Algorithms and Fundamental Data Structures
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Sorting Algorithms and Fundamental Data Structures
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Introducing Bubble Sorting
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Understanding Quick Sort
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Using Merge Sort
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Getting Started with Fundamental Data Structures
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Summary
3
Hash Tables and Binary Search Trees
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Hash Tables and Binary Search Trees
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Introducing Hash Tables
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Getting Started with Binary Search Trees
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Summary
4
Algorithm Design Paradigms
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Algorithm Design Paradigms
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Introducing Greedy Algorithms
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Getting Started with Divide and Conquer Algorithms
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Understanding Dynamic Programming
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Summary
5
String Matching Algorithms
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String Matching Algorithms
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Naive Search Algorithm
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Getting Started with the Boyer-Moore String Searching Algorithm
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Introducing Other String Matching Algorithms
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Summary
6
Graphs, Prime Numbers, and Complexity Classes
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Graphs, Prime Numbers, and Complexity Classes
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Representing Graphs
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Traversing a Graph
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Calculating Shortest Paths
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Prime Numbers in Algorithms
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Other Concepts in Graphs
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Understanding Complexity Classes of Problems
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Summary
7
Other Books You May Enjoy
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Calculating Shortest Paths

The shortest path is a path between two vertices so that the sum of the weights of the edges that constitute the path is minimized. The shortest path problem has many applications in the real world, from finding directions on mapping applications to minimizing the moves to solve a puzzle.

In this section, we shall look at two different strategies for computing shortest paths: one that finds the shortest paths from a single source to every other vertex in the graph, and another that finds shortest paths between all pairs of vertices in a graph.

Single Source Shortest Path: Dijkstra's Algorithm

When we explored BFS, we saw that it was able to solve the shortest path problem for unweighted graphs, or graphs whose edges have the same (positive) weight. What if we are dealing with weighted graphs? Can we do better? We shall see that Dijkstra's algorithm provides an improvement over the ideas presented in BFS and that it is an efficient algorithm for solving the single...

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