Book Image

Learning JavaScript Data Structures and Algorithms - Third Edition

Book Image

Learning JavaScript Data Structures and Algorithms - Third Edition

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 (22 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Representing a graph


There are a few ways in which we can represent graphs when it comes to data structures. There is no correct way of representing a graph among the existing possibilities. It depends on the type of problem you need to resolve, and the type of graph as well.

The adjacency matrix

The most common implementation is the adjacency matrix. Each node is associated with an integer, which is the array index. We will represent the connectivity between vertices using a two-dimensional array, as array[i][j] = = = 1 if there is an edge from the node with index i to the node with index j or as array[i][j] = = = 0 otherwise, as demonstrated by the following diagram:

Graphs that are not strongly connected (sparse graphs) will be represented by a matrix with many zero entries in the adjacency matrix. This means we would waste space in the computer memory to represent edges that do not exist. For example, if we need to find the adjacent vertices of a given vertex, we will have to iterate through...