As a JavaScript developer you might think you don’t need to learn about data structures or algorithms.

Did you know JavaScript itself (runtime + browser) uses things like a stack, a heap and a queue? The more you understand the JavaScript you use on a daily basis – really understand it, the better you can wield it’s power and make less mistakes. If you thought algorithms and data structures were just a computer science course that wasn’t necessary on a day to day basis as JavaScript developer, think again!

How To Read This Book

Each chapter covers an algorithm you might encounter in your work or at an interview. You can work through the algorithms one at a time or feel free to jump around.

What is an Algorithm

In this book, we’re going to write algorithms - the sets of steps that will solve specific problems for

us.

We constantly use algorithms in our everyday life. For example what if we’re somewhere on a street and want to get home to our apartment that is on the 20th floor? In order to achieve that we could do the following:

1. Take a WALK to your home.

2. Use STAIRS to go up to the 20th floor.

This is an algorithm. We’ve defined and used the set of steps that solve our task of getting home.

Contents

1. Introduction
2. How To Read This Book
3. Algorithms and Their Complexities
4. Linked List
5. Queue
6. Stack
7. Hash Table
8. Binary Search Tree (BST)
9. Binary Heap
10. Priority Queue
11. Graphs
12. Bit Manipulation
13. Factorial
14. Fibonacci Number
15. Primality Test
16. Is a power of two
17. Search. Linear Search.
18. Search. Binary Search.
19. Sets. Cartesian Product.
20. Sets. Power Set.
21. Sets. Permutations.
22. Sets. Combinations.
23. Sorting: Quicksort
24. Trees. Depth -First Search.
25. Trees. Breadth -First Search.
26. Graphs. Depth -First Search.
27. Graphs. Breadth -First Search.
28. Dijkstra's Algorithm

Appendix A: Quiz Answers

Appendix 8: Big O Times Comparison

Appendix C: Data Structures Operations Complexities

Appendix D: Array Sorting Algorithms Complexities