What this book covers

Chapter 1, JavaScript—A Quick Overview, covers the basics of JavaScript needed prior to learning data structures and algorithms. It also covers the setup of the development environment that we need for this book.

Chapter 2, Arrays, explains how to use the most basic and most used data structure, which are arrays. This chapter demonstrates how to declare, initialize, add, and remove elements from an array. It also covers how to use native JavaScript Array methods.

Chapter 3, Stacks, introduces the stack data structure, demonstrating how to create a stack and add and remove elements. It also demonstrates how to use stack to solve some computer science problems.

Chapter 4, Queues, covers the queue data structure, demonstrating how to create a queue and add and remove elements. It also demonstrates how to use queues to solve some computer science problems, and explains the major differences between queues and stacks.

Chapter 5, Linked Lists, explains how to create the linked list data structure from scratch using objects and the pointer concept. Besides covering how to declare, create, add, and remove elements, it also covers the various types of linked lists, such as doubly-linked lists and circular-linked lists.

Chapter 6, Sets, introduces the set data structure and how you can use it to store nonrepeated elements. It also explains the different types of set operations and how to implement and use them.

Chapter 7, Dictionaries and Hashes, explains the dictionary and hash data structures and the differences between them. This chapter covers how to declare, create, and use both data structures. It also explains how to handle collisions in hash, and the techniques to create better hash functions.

Chapter 8, Trees, covers the tree data structure and its terminology, focusing on Binary Search Tree data its methods to search, traverse, add, and remove nodes. It also introduces the next steps to dive into the world of trees, mentioning the tree algorithms that we should learn next.

Chapter 9, Graphs, introduces the amazing world of graphs and their application in real-world problems. This chapter covers the most common graph terminology, different ways of representing a graph, and how to traverse graphs using the Breadth-First-Search and Depth-First-Search algorithms and their applications.

Chapter 10 , Sorting and Searching Algorithms , explores the most used sorting algorithms, such as the Bubble sort (and its improved version), Selection sort, Insertion sort, Merge sort, and Quick sort. It also covers searching algorithms, such as the sequential and binary search.

Chapter 11 , Patterns of Algorithm , introduces some algorithm techniques and some of the most famous algorithms. It covers the recursion concept and some advanced algorithm techniques, such as dynamic programming and greedy algorithms.

Chapter 12 , Algorithm Complexity , introduces the Big-O notation and its concepts along with a cheat sheet of the complexity of the algorithms implemented in this book. It covers an introduction to NP-Completeness problems and heuristic solutions. Finally it explains how to take your algorithm knowledge to the next level.