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Learning JavaScript Data  Structures and Algorithms

Learning JavaScript Data Structures and Algorithms - Third Edition

By : Loiane Avancini
3.1 (9)
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Learning JavaScript Data  Structures and Algorithms

Learning JavaScript Data Structures and Algorithms

3.1 (9)
By: Loiane Avancini

Overview of this book

A data structure is a particular way of organizing data in a computer to utilize resources efficiently. Data structures and algorithms are the base of every solution to any programming problem. With this book, you will learn to write complex and powerful code using the latest ES 2017 features. Learning JavaScript Data Structures and Algorithms begins by covering the basics of JavaScript and introduces you to ECMAScript 2017, before gradually moving on to the most important data structures such as arrays, queues, stacks, and linked lists. You will gain in-depth knowledge of how hash tables and set data structures function as well as how trees and hash maps can be used to search files in an HD or represent a database. This book serves as a route to take you deeper into JavaScript. You’ll also get a greater understanding of why and how graphs, one of the most complex data structures, are largely used in GPS navigation systems in social networks. Toward the end of the book, you’ll discover how all the theories presented in this book can be applied to solve real-world problems while working on your own computer networks and Facebook searches.
Table of Contents (17 chapters)
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Self-balancing trees


Now that you have learned how to work with BST, you can dive into the study of trees if you want to.

BST has a problem: depending on how many nodes you add, one of the edges of the tree can be very deep, meaning a branch of the tree can have a high level and another branch can have a low level, as shown in the following diagram:

This can cause performance issues when adding, removing, and searching for a node on a particular edge of the tree. For this reason, there is a tree called the Adelson-Velskii and Landi's tree (AVL tree). The AVL tree is a self-balancing BST, which means the height of both the left and right subtrees of any node differ by 1 at most. You will learn more about the AVL tree in the following topic.

Adelson-Velskii and Landi’s tree (AVL tree)

The AVL tree is a self-balancing tree, meaning the tree tries to self-balance whenever a node is added to it or removed from it. The height of the left or right subtree of any node (and any level) differs by 1 at...

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Learning JavaScript Data  Structures and Algorithms
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