Best Books for Learning Data Structures and Algorithms

books for data structures and algorithms

Best Books for Learning Data Structures and Algorithms

Key Points

  • Data structures are different ways that data is arranged to make saving and accessing data more straightforward.
  • Algorithms are the procedures for how to achieve a goal and provide a series of clear instructions to your computer.
  • Data structures rely on algorithms to interact with them and maintain their format.
  • The best books for learning data structures and algorithms include ‘Introduction to Algorithms’, ‘Grokking Algorithms’, ‘A Common Sense Guide to Data Structures and Algorithms’, ‘Algorithms’, and ‘The Algorithm Design Manual’.

When it comes to computer science concepts, books are sometimes overshadowed by other learning methods like online tutorials. If you’re a programmer or system designer at any level, you’re likely familiar with some data structures and algorithms. Sometimes, you may not even realize you’re using data structures or algorithms. 

Data structures and algorithms are usually discussed as a pair. This is because they are very interlinked. Data structures make use of algorithms, and algorithms are what make data structures useful. 

If you’ve read my article on how to become a software engineer, you know that I made a pretty big point of learning data structures and algorithms — that’s because they are one of the fundamental building blocks of computer science.

What Are Data Structures?

Data structures are different ways that data is arranged to make saving and accessing data more straightforward. Data structures define the relationships between different data points in a collection and how you can retrieve and manipulate that data.

Common data structures you can see in almost all languages are things like arrays, objects, stacks, lists, etc. The benefit of these is a clear and consistent way of interacting with that data. Even primitive types of the language you use are data structures. 

Each data structure has benefits and weaknesses depending on the use case. Depending on what you need to achieve with your data, there should be an optimal type of data structure to house and organize it. Knowing how they work and which one to use is a vital skill for a computer science student. I’m not going to go too into detail here, since we covered data structures in much greater detail in this article. Feel free to check it out.

What Are Algorithms?

Algorithms are the procedures for how to achieve a goal. This is an abstract way to describe algorithms, but they’re a great way to simplify a complex process. An algorithm is a way to define a set of repeatable steps to achieve a specific output given an input. 

Think of algorithms as instruction sets. Given an input, an algorithm provides a series of clear instructions to your computer to achieve a repeatable result. Imagine you’re baking a cake. 

To begin, you need the correct ingredients to start. From there, you have a specific set of instructions to put the ingredients together and end up with a cake. If you have slightly different ingredients, you may have a strawberry or chocolate cake. The “algorithm” to make them is the same, and the output is still similar. 

Algorithms operate the same. If you have problems like how to sort a list, search for a value, or manipulate a data structure, then you’ll make use of an algorithm.

Data structures rely on whatever data you’re trying to manipulate being input/read/removed in a way that is compatible with the structure. If you’re using a data structure, then you’re using algorithms to interact with it.

Algorithms allow data structures to maintain their format. The benefit of data structures is how you can maintain and make use of them through algorithms. 

Programming requires at least a basic understanding of how both of these concepts work. Without data structures to maintain information and algorithms to operate on this data, development would be nearly impossible.

Now, I know we’re trying to steer you toward books, but quick tutorials like the one below do a good job of explaining the basics in a few minutes:

Top Books for Data Structures and Algorithms

Data structures and algorithms abstract away a lot of work for developers to allow us to focus on solutions first. The issue is that sometimes, these existing abstractions aren’t entirely optimal to solve every situation. Some patterns lend themselves better to certain issues. 

Not only is it important to understand existing algorithms, but to understand how they are built and how you can build your own. Online tutorials are great for getting a broad overview or seeing someone implement a solution quickly, but if you want something that you can really dive into and reference at your own pace, books are a great answer.

Here, we’ll list some of our favorite books and some recommendations from around the web so you can find the right resource for you. These are books that have helped me personally learn data structures and algorithms, and many of them have been recommended by software engineers with years or decades of experience.

To give you a quick rundown, here are the best books for learning data structures and algorithms:

Best Overall – Introduction to Algorithms – Cormen, Leiserson, Rivest, Stein

Best Overall
Introduction to Algorithms, fourth edition
  • Excellent reference material
  • Wide range of topics
  • Theory driven
  • Covers a broad range of algorithms in depth
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02/26/2024 04:11 am GMT

Starting with one of the most divisive picks, Introduction to Algorithms is almost guaranteed to be mentioned when discussing learning materials. Love it or hate it, Introduction to Algorithms offers one of the most comprehensive guides available. 

This book is the most encyclopedic among the other materials. Not only does this act as a great learning resource, but also as reference material that you can keep going back to when you need help.

Thanks to the four authors and various updates, this 2022 edition is a comprehensive look at many established patterns and even touches on modern topics like AI and machine learning.

Introduction to Algorithms is known to be a bit intimidating. Some find the straightforward nature of the book to be overwhelming. For an introduction book, it can feel like there’s some missing information if you’re new to the concepts. 

Overall, this is still a great resource and pairs well with any other materials listed here — it is a must-buy for any programmer or developer if you want something that will stay relevant for years to come.

Wide range of topicsDifficult to read through
Language agnostic explanationsRequires a familiarity with base concepts
Theory drivenNot beginner friendly
Great as a reference Book
Updated in 2022

Check out Introduction to Algorithms on Amazon.

Best Book for Beginners – Grokking Algorithms – Aditya Bhargava

Grokking Algorithms: An Illustrated Guide
  • Learn how to apply common algorithms to practical, everyday problems
  • Over 400 pictures with detailed walkthroughs
  • Python-based code samples
  • The author has a dual background in Computer Science and Fine Arts
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02/26/2024 04:20 am GMT

If Introduction to Algorithms feels a bit too intimidating, Grokking Algorithms is another highly recommended learning tool. This is a fully illustrated guide that aims to take you from simple and common algorithms to more advanced concepts. 

This book is roughly a fifth of the size of Introduction to Algorithms but aims to be a practical guide to getting started as opposed to an encyclopedia. This is a book you can reasonably expect to read cover to cover in a short amount of time.

This book uses Python for its examples rather than pseudocode, so you’ll be able to start implementing and using the examples directly from the book. Illustrations are provided for almost every algorithm, making conceptualization easier. 

Unlike the previous recommendation, this is a great beginner’s book. The aim is to build foundational knowledge and get you prepared for further materials down the line. If you’re just starting your journey, definitely pick this one up.

Easy readA bit short
Fantastic illustrationsLimited coverage of concepts
Designed to teachExamples exclusive to Python
Great for beginners

Check out Grokking Algorithms on Amazon.

Best Multilanguage Book – A Common Sense Guide to Data Structures and Algorithms – Jay Wengrow

Best Multilanguage Book
A Common-Sense Guide to Data Structures and Algorithms, Second Edition: Level Up Your Core Programming Skills
  • Simple terminology
  • Lots of example problems
  • JavaScript, Python, and Ruby discussed
  • Use Big O notation
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02/26/2024 04:55 am GMT

Landing somewhere in the middle between a comprehensive guide and a beginner book, A Common Sense Guide to Data Structures and Algorithms is the book for programmers who are proficient but skipped (or forgot) the formal computer science fundamentals. 

As important as math is, it can get tiresome to need a mathematics degree to even read the learning materials. This book aims to take these complex explanations and boil them down to plain English explanations.

Examples are offered in JavaScript, Python, and Ruby, so you should be able to implement the algorithms and data structures in almost any language you choose. This book also offers plenty of exercise problems to test yourself with and get a practical and functional understanding by actually using the concepts described. 

Simple terminologySome important math may be skipped
Examples in most major languagesMade for a mid-level understanding
Lots of example problems
Updated in 2020

Check out A Common Sense Guide to Data Structures and Algorithms on Amazon.

Best Book for Advanced Learners – Algorithms – Robert Sedgewick, Kevin Wayne

Best for Advanced Learners
Algorithms (4th Edition)
  • Written in textbook style
  • Dedicated companion site
  • Wide range of topics
  • Java/C++ specific
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02/26/2024 10:56 am GMT

Don’t let the simplicity of this book’s outer appearance fool you. Algorithms by Sedgewick and Wayne is meant to be a textbook to teach you on a much deeper level. This book thrives on college campuses and in many courses around the world. 

This book is an introductory example that is great for students and those of us who lack a CS background. The textbook style of this book means you’ll have plenty of examples available, and even the option of accessing a companion site to act as a course supplement.

Free online courses exist as well, so beyond the book, you’ll have access to a wealth of resources that work in tandem with it. It is a little on the pricey side, being a full textbook, but if you’re looking to get deep knowledge and willing to put in the effort, this book will help you exceed expectations.

The examples here are in Java, (C++ Option also available), so it may be a bit hard to start with or translate to other languages. If you’re fine working in different languages, this might not be an issue. Even so, this book is a great deep dive and something valuable to keep around if you are looking for a solid study reference.

Dedicated companion siteJava/C++ specific
Wide range of topicsLast updated in 2011
School-style learning experienceLots of paid & free courses are available

Check out Algorithms on Amazon.

Best Book for Practical Learners – The Algorithm Design Manual – Steve Skiena

Best Book for Practical Learners
The Algorithm Design Manual (Texts in Computer Science)
  • College-style textbook
  • Full-color illustrations with examples
  • Updated third edition
  • Provides full online support for lecturers
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02/26/2024 11:16 am GMT

As important as it is to understand existing algorithms and data structures, actually building them is a different story. The Algorithm Design Manual aims to teach problem-solving with algorithms rather than just explaining each one’s function. 

If you’re a practical learner, then this will be a great experience. Another college-style textbook, The Algorithm Design Manual aims to provide tools on how to solve problems. This book also acts as the best of both worlds. Let me explain:

The first half of this book covers learning materials for designing, analyzing, and implementing algorithms into your code. The second part acts as a reference sheet with 75 common algorithm implementations in both C, C++, and Java.

Plus, this book also includes illustrations alongside the examples and a companion site with video lectures and slide decks available to help guide your learning.

Requires solid code and mathematics knowledgeJava/C/C++ specific
Companion siteNot beginner friendly
IllustrationsRequires solid code & Mathematics knowledge
Updated in 2020
Plenty of practice problems

Check out The Algorithm Design Manual on Amazon.

Best Book for Intermediate Learners – Data Structures and Algorithms Made Easy – Narasimha Karumanchi

Best for Intermediate Learners
Data Structures and Algorithms Made Easy: Data Structures and Algorithmic Puzzles
  • Undergraduate level
  • Beginner to intermediate focus
  • Overall great resource
  • Great reference manual
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02/26/2024 11:35 am GMT

Last up in our recommendations is another well-regarded book. Data Structures and Algorithms Made Easy is a great all-round pick. This book functions as a technical guide, a learning tool, and a reference material. 

Aimed towards those at an undergraduate level, you’ll still be getting a beginner’s explanation with the understanding of a base level of understanding. From fundamentals to implementations, you’ll be interview-ready after covering this material.

The advantage here is this material is made to take you from the beginner level to an intermediate understanding. Even someone who has taken an intro course or has a base understanding will benefit from this.

Overall great resourceC/C++ specific
Works great as a companion bookRequires base CS/Math knowledge
Beginner to intermediate focusLast updated in 2016
Wide range of topics

Check out Data Structures and Algorithms Made Easy on Amazon.

How to Pick the Best Book for Learning Data Structures and Algorithms

There are so many books on this topic out there — how do you pick the best ones? And how did we come to these picks?

To start, you want to consider your current skill level and understanding of computer science. Are you a complete beginner? Then a book like Grokking Algorithms will probably be the best choice. Are you already familiar with important concepts and want something that won’t hold back on the technical details? Then Algorithms by Sedgewick and Wayne will likely be right up your alley.

Also, consider if you want a book that has examples in the specific language that you’re comfortable with. Some books only have examples in C# or Java, which might be intimidating for a beginner. Whereas other books offer a mix of examples in Python, JavaScript, Ruby, and other languages.

What to Know Before Buying a Book for Data Structures and Algorithms

You don’t need to know much before you jump into data structures and algorithms. If you check out this computer science roadmap, you’ll see that both of these concepts are brought up fairly early. You could pick a language first, but as I’ve said repeatedly, you shouldn’t overthink this decision either.

You’ll want to start with something simple. If you already know a little bit of a language like JavaScript or Python, start off with arrays and methods. Then you can slowly work on more complex topics like hash maps.

The only thing you need to know before buying a book on the subject is generally what these terms mean. You should have a rudimentary knowledge, just to be sure that you’re not buying a book that is too far out of your skill level.

Focused millennial african american student in glasses making notes writing down information from book in cafe preparing for test or exam, young serious black man studying or working in coffee house
Keep your data structures and algorithms book of choice on hand to reference when you are working on real-world projects or practice exercises on your computer.

Using One of These Books: What it’s Like and How to Get the Most Out of It.

Once you have landed on the ideal book to start off, how do you get the most out of it? This really depends on the book. If you opt for a shorter book that you can read through in one or two sessions, you’ll do your best to keep this book handy to reread as the occasional refresher.

If you don’t understand certain concepts from your reading, get out there and practice the concepts you do know — move on for a bit. Then circle back around to see if any more information sticks on the second read-through.

For longer, more reference-style books, it will probably be too intimidating to tackle everything at once. These are your college course textbooks, with hundreds of pages, chock full of a lifetime’s worth of information. You definitely won’t read through these in one sitting. So, keep them handy, bookmark spots of interest, and refer back to them as you work on real-world projects and practice sets.

Frequently Asked Questions

What is the best source to learn data structures and algorithms?

Depending on your skill level, there are several options. “Introduction to Algorithms” is the most comprehensive book, but requires a lot of foundational knowledge. “Data Structures and Algorithms Made Easy,” “Algorithms,” and “Grokking Algorithms” are better for beginners and offer different experiences as well.

What is the fastest way to learn data structures and algorithms?

Data structures and algorithms are extremely varied, so try to build a varied curriculum with not just books, but online tutorials and exercises too. Identify your core issues, see what patterns are best for those, and focus your learning there.

Can I learn data structures and algorithms from books?

Yes! Many books cover these topics from the entry-level to professional and everything in between. Look for books that match your skill level and method of learning. Many books also provide additional resources or work well with others.

Is C++ best for data structures and algorithms?

The thing about data structures and algorithms is that they are not language-specific. You can apply these philosophies to any language. Learn these concepts in your preferred language if possible, but you should be able to apply these concepts universally.

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