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

Divide and conquer


In Chapter 13, Sorting and Searching Algorithms, we learned how to develop the merge and quick sort algorithms. What both sorting solutions have in common is that they are divide and conquer algorithms. Divide and conquer is one of the approaches to algorithm design. It breaks the problem into small subproblems that are similar to the original problem, it solves the subproblems recursively, and combines the solutions of the subproblems to solve the original problem.

The divide and conquer algorithm can be split into three parts:

  1. Divide the original problem into smaller subproblems (smaller instances of the original problem).
  2. Conquer the smaller subproblems by solving them with recursive algorithms that return the solution for the subproblems. The base case of the recursive algorithm solves and returns the solution for the smallest subproblem.
  3. Combine the solutions of the subproblems into the solution for the original problem.

As we have already covered the two most famous divide...