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Hands-On Data Structures and Algorithms with JavaScript
Hands-On Data Structures and Algorithms with JavaScript

Hands-On Data Structures and Algorithms with JavaScript: Write efficient code that is highly performant, scalable, and easily testable using JavaScript

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Hands-On Data Structures and Algorithms with JavaScript

Creating Queues for In-Order Executions

A queue is a programming construct that bears a heavy resemblance to real-world queues, for example, a queue at the movie theater, ATMs, or the bank. Queues, as opposed to stacks, are first-in first-out (FIFO), so whatever goes in first comes out first as well. This is especially helpful when you would like to maintain data in the same sequence in which it flows in.

A more computer/scientific definition of a queue would be as follows: 

An abstract data collection in which the elements can be added to the back called enqueue and removed from the front called dequeue which makes it a FIFO data structure.

Of course, having only enqueue and dequeue operations may be enough for the majority of cases to cover a wider spectrum of issues that we may encounter; however, we can expand the API and make our queue future...

Types of queue

Before we begin understanding queues, let's quickly take a look at the types of queues that we may want to use in our applications:

  • Simple queue: In a simple FIFO queue, the order is retained and data leaves in the same order in which it comes in
  • Priority queue: A queue in which the elements are given a predefined priority
  • Circular queue: Similar to a simple queue, except that the back of the queue is followed by the front of the queue
  • Double ended queue (Dequeue): Similar to the simple queue but can add or remove elements from either the front or the back of the queue

Implementing APIs

Implementing an API is never as easy as it seems, as discussed earlier. When making generic classes, we can never predict what kinds of a situation our queue is going to be used in. With that in mind, let's create a very generic API for our queue and expand it in future as we see fit. Some of the most common operations that we can add to the queue are as follows:

  •  add(): Pushes an item to the back of the queue
  •  remove(): Removes an item from the start of the queue
  •  peek(): Shows the last item added to the queue
  •  front(): Returns the item at the front of the queue
  •  clear(): Empties the queue
  •  size(): Gets the current size of the queue

Creating a queue

Of the four types of the queue that we have discussed earlier, first, we will implement a simple queue and then move on to modify it for each type of the subsequent queue.

A simple queue

Similar to a stack, we will create a queue using the following steps:

  1. Define a constructor():
class Queue {
constructor() {

}
}
  1. We will be using WeakMap() for in-memory data storage just like we did for stacks: 
    const qKey = {};
const items = new WeakMap();

class Queue {
constructor() {

}
}
  1. Implement the methods described previously in the API:
var Queue = (() => {
const qKey = {};
const items = new WeakMap();

class Queue {

constructor() {
...

Use cases for queues

Before we start off with use cases, we will need a base starting point in the form of a Node.js application. To create one, ensure that you have the latest Node.js installed:

node -v

This should show you your currently installed Node.js version; if it does not, then download and install the latest version of Node.js from https://nodejs.org/en.

Creating a Node.js application

To start off a sample Node.js project, simply create a project folder first and then run the following command from that folder:

npm init

On running this command, Node will prompt you with a series of questions, which you can either fill or leave blank:

Once the blank application is created, all you see is a file called...

Comparing performance

Earlier, we saw how we can simply swap out a simple queue for a priority queue and not worry about the functional change that it might cause; similarly, we can swap out priority queues for a higher-performant variant of them: circular dequeues.

Before we start working on a comparison, we will need to discuss circular queues and why we need them. 

The difference between a circular queue and a simple queue is that the back of the queue is followed by the front of the queue. That being said, they are not functionally different. They still perform the same operations, and produce the same results; you might be wondering where exactly they differ and what's the point if the end result is the same.

In JavaScript arrays, memory locations are contiguous. So, when creating a queue and performing operations such as remove(), we will need to worry about...

Summary

With that, we conclude this chapter on queues. We learned about simple, priority, and circular queues and it's double-ended variant. We also learned when to apply them based on use cases and we saw with example, how we can leverage the power of benchmarking any algorithm or data structure as needed. In the next chapter, we will be putting sets, maps, and hashes under the microscope to understand their internal workings and see what situations they can be useful in.

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Key benefits

  • A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental JavaScript data structures
  • Get a better understanding of advanced concepts such as space and time complexity to optimize your code
  • Focus more on solving the business problem and less on the technical challenges involved

Description

Data structures and algorithms are the fundamental building blocks of computer programming. They are critical to any problem, provide a complete solution, and act like reusable code. Using appropriate data structures and having a good understanding of algorithm analysis are key in JavaScript to solving crises and ensuring your application is less prone to errors. Do you want to build applications that are high-performing and fast? Are you looking for complete solutions to implement complex data structures and algorithms in a practical way? If either of these questions rings a bell, then this book is for you! You'll start by building stacks and understanding performance and memory implications. You will learn how to pick the right type of queue for the application. You will then use sets, maps, trees, and graphs to simplify complex applications. You will learn to implement different types of sorting algorithm before gradually calculating and analyzing space and time complexity. Finally, you'll increase the performance of your application using micro optimizations and memory management. By the end of the book you will have gained the skills and expertise necessary to create and employ various data structures in a way that is demanded by your project or use case.

Who is this book for?

If you are a JavaScript developer looking for practical examples to implement data structures and algorithms in your web applications, then this book is for you. Familiarity with data structures and algorithms will be helpful to get the most out of this book.

What you will learn

  • Build custom Back buttons embedded within your application
  • Build part of a basic JavaScript syntax parser and evaluator for an online IDE
  • Build a custom activity user tracker for your application
  • Generate accurate recommendations for credit card approval using Decision Trees
  • Simplify complex problems using a graphs
  • Increase the performance of an application using micro-optimizations

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 30, 2018
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781788398558
Vendor :
Netscape
Category :
Languages :

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Product Details

Publication date : Jan 30, 2018
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781788398558
Vendor :
Netscape
Category :
Languages :

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Table of Contents

10 Chapters
Building Stacks for Application State Management Chevron down icon Chevron up icon
Creating Queues for In-Order Executions Chevron down icon Chevron up icon
Using Sets and Maps for Faster Applications Chevron down icon Chevron up icon
Using Trees for Faster Lookup and Modifications Chevron down icon Chevron up icon
Simplify Complex Applications Using Graphs Chevron down icon Chevron up icon
Exploring Types of Algorithms Chevron down icon Chevron up icon
Sorting and Its Applications Chevron down icon Chevron up icon
Big O Notation, Space, and Time Complexity Chevron down icon Chevron up icon
Micro-Optimizations and Memory Management Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
(3 Ratings)
5 star 33.3%
4 star 33.3%
3 star 33.3%
2 star 0%
1 star 0%
Prashanth Naik Aug 19, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book has a strong recipe for Data Structures and in-depth tutorial about Javascript. This has mostly everything you want to know if you want to understand DS. Helped a lot during the interview stage. Thanks, Kashyap.
Amazon Verified review Amazon
Webia1 Sep 01, 2019
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
einige Wunschbereiche sind dünn aber jetzt habe ich keine Zeit explizit darauf einzugehen, sorry,..
Amazon Verified review Amazon
Amazon Customer Nov 30, 2018
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
The grammar in this book is not great, but I do not think the author is a native English speaker. Some areas are better than others. I found the book to be practical, but its frustrating trying to figure out what the author means.. You will not find refuge in Learning Javascript Data Structures and Algorithms by Loiane Groner as that book is worse. I'll leave a 3 for effort, it probably should be 2 seeing that this book costed about 50.00. I doubt I would buy a 2nd Edition.
Amazon Verified review Amazon
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