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Java 9 Data Structures and Algorithms

Java 9 Data Structures and Algorithms

By : Ray Chawdhuri
2.3 (3)
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Java 9 Data Structures and Algorithms

Java 9 Data Structures and Algorithms

2.3 (3)
By: Ray Chawdhuri

Overview of this book

Java 9 Data Structures and Algorithms covers classical, functional, and reactive data structures, giving you the ability to understand computational complexity, solve problems, and write efficient code. This book is based on the Zero Bug Bounce milestone of Java 9. We start off with the basics of algorithms and data structures, helping you understand the fundamentals and measure complexity. From here, we introduce you to concepts such as arrays, linked lists, as well as abstract data types such as stacks and queues. Next, we’ll take you through the basics of functional programming while making sure you get used to thinking recursively. We provide plenty of examples along the way to help you understand each concept. You will also get a clear picture of reactive programming, binary searches, sorting, search trees, undirected graphs, and a whole lot more!
Table of Contents (13 chapters)
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12
Index

Chapter 1. Why Bother? – Basic

Since you already know Java, you have of course written a few programs, which means you have written algorithms. "Well then, what is it?" you might ask. An algorithm is a list of well-defined steps that can be followed by a processor mechanically, or without involving any sort of intelligence, which would produce a desired output in a finite amount of time. Well, that's a long sentence. In simpler words, an algorithm is just an unambiguous list of steps to get something done. It kind of sounds like we are talking about a program. Isn't a program also a list of instructions that we give the computer to follow, in order to get a desired result? Yes it is, and that means an algorithm is really just a program. Well not really, but almost. An algorithm is a program without the details of the particular programming language that we are coding it in. It is the basic idea of the program; think of it as an abstraction of a program where you don't need to bother about the program's syntactic details.

Well, since we already know about programming, and an algorithm is just a program, we are done with it, right? Not really. There is a lot to learn about programs and algorithms, that is, how to write an algorithm to achieve a particular goal. There are, of course, in general, many ways to solve a particular problem and not all ways may be equal. One way may be faster than another, and that is a very important thing about algorithms. When we study algorithms, the time it takes to execute is of utmost importance. In fact, it is the second most important thing about them, the first one being their correctness.

In this chapter, we will take a deeper look into the following ideas:

  • Measuring the performance of an algorithm
  • Asymptotic complexity
  • Why asymptotic complexity matters
  • Why an explicit study of algorithms is important
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