Book Image

Hands-On Data Structures and Algorithms with JavaScript

By : Kashyap Mukkamala
Book Image

Hands-On Data Structures and Algorithms with JavaScript

By: Kashyap Mukkamala

Overview of this book

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.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
PacktPub.com
Contributors
Preface
5
Simplify Complex Applications Using Graphs
Index

Examples of time complexity


Let's now examine some examples of time complexity calculations, since in 99% of the cases we need to know the maximum time a function might take to execute; we will be mostly analyzing the worst case time complexity, that is, the upper bound of the rate of growth based on the input of a function.

Constant time

A constant time function is one which takes the same amount of time to execute, irrespective of the size of the input that is passed into the function:

function square(num) {
    return num*num;
}

The preceding code snippet is an example of a constant time function and is denoted by O(1). Constant time algorithms are the most sought out algorithms for obvious reasons, such as them running in a constant time, irrespective of the size of the input. 

Logarithmic time

A Logarithmic time function is one in which the time of execution is proportional to the logarithm of the input size. Consider the following example:

for(var i = 1; i < N; i *= 2) {
    // O(1) operations...