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Beginning Java Data Structures and Algorithms

Beginning Java Data Structures and Algorithms

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

Beginning Java Data Structures and Algorithms

4.6 (10)
By: James Cutajar

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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Using Merge Sort

Although the quicksort on average is pretty fast, it still has the theoretical worst time complexity of O(n²). In this section, we shall examine another sorting algorithm, called merge sort, in which the worst time complexity is O(n log n). Similar to quick sort, merge sort belongs to the divide and conquer class of algorithms.

Merge sort can be summarized in three simple steps as follows: 

  1. Split the array in the middle
  2. Recursively sort each part separately
  3. Merge the two sorted parts together

In the following section, we will develop the preceding steps gradually, at each turn slowly building our understanding of how merge sorting works.

Although merge sort is theoretically faster than quick sort, in practice, some implementations of quick sort can be more efficient than merge sort. Additionally, the merge sort uses about O(n) memory...
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