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Learning JavaScript Data Structures and Algorithms - Third Edition

Java, JavaScript, JScript, Perl Java, JavaScript, JScript, Perl

Learning JavaScript Data Structures and Algorithms - Third Edition

Autor: Loiane Groner
Broj strana: 426
ISBN broj: 9781788623872
Godina izdanja: 2019.

Pregleda (30 dana / ukupno): 27 / 419

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  • Declare, initialize, add, and remove items from arrays, stacks, and queues
  • Create and use linked lists, doubly linked lists, and circular linked lists
  • Store unique elements with hash tables, dictionaries, and sets
  • Explore the use of binary trees and binary search trees
  • Sort data structures using algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quick sort
  • Search elements in data structures using sequential sort and binary search

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.

  • Implement common data structures and the associated algorithms along with the context in which they are used
  • Master existing JavaScript data structures such as arrays, sets, and maps, and learn how to implement new ones such as stacks, linked lists, trees, and graphs in ES 8
  • Develop abstract data types to make JavaScript a more flexible and powerful programming language

Table of contents

1 JavaScript – A Quick Overview
JavaScript data structure and algorithms
Setting up the environment
JavaScript basics
Debugging and tools

2 ECMAScript and TypeScript Overview
ECMAScript or JavaScript?
ECMAScript 2015+ functionalities
Introducing TypeScript

3 Arrays
Why should we use arrays?
Creating and initializing arrays
Adding elements
Removing elements
Adding and removing elements from a specific position
Two-dimensional and multi-dimensional arrays
References for JavaScript array methods
The TypedArray class
Arrays in TypeScript

4 Stacks
Creating a JavaScript data structure and algorithm library
The stack data structure
Creating a JavaScript object-based Stack class
Protecting the internal elements of the data structure
Solving problems using stacks

5 Queues and Deques
The queue data structure
The deque data structure
Solving problems using queues and deques

6 Linked Lists
The linked list data structure
Doubly linked lists
Circular linked lists
Sorted linked lists
Creating the StackLinkedList class

7 Sets
Structuring a dataset
Creating a Set class
Set operations
ECMAScript 2015 – the Set class
Multisets or bags

8 Dictionaries and Hashes
The dictionary data structure
The hash table
The ES2015 Map class
The ES2015 WeakMap and WeakSet classes

9 Recursion
Understanding recursion
Calculating the factorial of a number
The Fibonacci sequence
Why use recursion? Is it faster?

10 Trees
The tree data structure
Tree terminology
The binary and binary search trees
Tree traversal
Searching for values in a tree
Self-balancing trees

11 Binary Heap and Heap Sort
The binary heap data structure
The heap sort algorithm

12 Graphs
Graph terminology
Representing a graph
Creating the Graph class
Graph traversals
Shortest path algorithms
Minimum spanning tree (MST)

13 Sorting and Searching Algorithms
Sorting algorithms
Searching algorithms
Shuffle algorithms

14 Algorithm Designs and Techniques
Divide and conquer
Dynamic programming
Greedy algorithms
Backtracking algorithms
Introduction to functional programming

15 Algorithm Complexity
Big O notation
Having fun with algorithms


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