JavaScript Data Structures and Algorithms: An Introduction to Understanding And Implementing Core Data Structure and Algorithm Fundamentals

  • 3h 11m
  • Sammie Bae
  • Apress
  • 2019

Explore data structures and algorithm concepts and their relation to everyday JavaScript development. A basic understanding of these ideas is essential to any JavaScript developer wishing to analyze and build great software solutions. You'll discover how to implement data structures such as hash tables, linked lists, stacks, queues, trees, and graphs. You'll also learn how a URL shortener, such as bit.ly, is developed and what is happening to the data as a PDF is uploaded to a webpage. This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching. It is crucial for JavaScript developers to understand how data structures work and how to design algorithms. This book and the accompanying code provide that essential foundation for doing so. With JavaScript Data Structures and Algorithms you can start developing your knowledge and applying it to your JavaScript projects today.

What You'll Learn

Review core data structure fundamentals: arrays, linked-lists, trees, heaps, graphs, and hash-table

Review core algorithm fundamentals: search, sort, recursion, breadth/depth first search, dynamic programming, bitwise operators

Examine how the core data structure and algorithms knowledge fits into context of JavaScript explained using prototypical inheritance and native JavaScript objects/data types

Take a high-level look at commonly used design patterns in JavaScript

Who This Book Is For

Existing web developers and software engineers seeking to develop or revisit their fundamental data structures knowledge; beginners and students studying JavaScript independently or via a course or coding bootcamp.

In this Book

  • Big-O Notation
  • JavaScript: Unique Parts
  • JavaScript Numbers
  • JavaScript Strings
  • JavaScript Arrays
  • JavaScript Objects
  • JavaScript Memory Management
  • Recursion
  • Sets
  • Searching and Sorting
  • Hash Tables
  • Stacks and Queues
  • Linked Lists
  • Caching
  • Trees
  • Heaps
  • Graphs
  • Advanced Strings
  • Dynamic Programming
  • Bit Manipulation
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