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Learning JavaScript Data  Structures and Algorithms

You're reading from   Learning JavaScript Data Structures and Algorithms Write complex and powerful JavaScript code using the latest ECMAScript

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788623872
Length 426 pages
Edition 3rd Edition
Languages
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Author (1):
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Loiane Avancini Loiane Avancini
Author Profile Icon Loiane Avancini
Loiane Avancini
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Table of Contents (17) Chapters Close

Preface 1. JavaScript – A Quick Overview FREE CHAPTER 2. ECMAScript and TypeScript Overview 3. Arrays 4. Stacks 5. Queues and Deques 6. Linked Lists 7. Sets 8. Dictionaries and Hashes 9. Recursion 10. Trees 11. Binary Heap and Heap Sort 12. Graphs 13. Sorting and Searching Algorithms 14. Algorithm Designs and Techniques 15. Algorithm Complexity 16. Other Books You May Enjoy

The binary and binary search trees


A node in a binary tree has two children at most: one left child and one right child. This definition allows us to write more efficient algorithms to insert, search, and delete nodes to/from a tree. Binary trees are largely used in computer science.

A binary search tree (BST) is a binary tree, but it only allows you to store nodes with lesser values on the left-hand side and nodes with greater values on the right-hand side. The diagram in the previous topic exemplifies a binary search tree.

This will be the data structure that we will work on in this chapter.

Creating the Node and BinarySearchTree classes

Let’s start by creating our Node class that will represent each node of our binary search tree using the following code:

export class Node {
  constructor(key) {
    this.key = key; // {1} node value
    this.left = null; // left child node reference
    this.right = null; // right child node reference
  }
}

The following diagram exemplifies how a binary search...

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