A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills

Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today’s web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby.

Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You’ll even encounter a single keyword that can give your code a turbo boost. Jay Wengrow brings to this book the key teaching practices he developed as a web development bootcamp founder and educator.

Use these techniques today to make your code faster and more scalable.

Table of Contents

Chapter 1. Why Data Structures Matter
Chapter 2. Why Algorithms Matter
Chapter 3. Oh Yes! Big O Notation
Chapter 4. Speeding Up Your Code With Big O
Chapter 5. Optimizing Code With And Without Big O
Chapter 6. Optimizing For Optimistic Scenarios
Chapter 7. Blazing Fast Lookup With Hash Tables
Chapter 8. Crafting Elegant Code With Stacks And Queues
Chapter 9. Recursively Recurse With Recursion
Chapter 10. Recursive Algorithms For Speed
Chapter 11. Node-Based Data Structures
Chapter 12. Speeding Up All The Things With Binary Trees
Chapter 13. Connecting Everything With Graphs
Chapter 14. Dealing With Space Constraints