Data Structures and Algorithms books are often taught as textbooks in various universities, colleges, and Computer Science degree courses, yet, when you put programmers in a situation, where they need to find and decide, which data structures and algorithms to use to solve a problem, they struggle.
Since data structures and algorithms are the core of any programming problem, it becomes extremely important for programmers to master them even if you have learned well during academics. In this article, I am sharing my favourite books on data structures and algorithms, which I think are a great read and can help every programmer to master data structure and algorithms.
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Introduction to Algorithms provides a comprehensive overview and guide to algorithms at large. It acts as an encyclopedic reference for modern algorithms, extensively covering everything between theory and practice in over 1,000 pages.
The book is very practical, presenting problems with diagrams and proofs, implementing algorithms, and analyzing the theory behind the results. “Introduction” assumes reasonable familiarity with math and data structures, but eager readers will have a lot to chew on.
Author Thomas Cormen’s seeks to take away the mystery of technology and unveils the secrets behind its inner workings. So many things we take for granted, like automated GPS routes or internet encryption, all use applied algorithms to operate.
The book explains how computers use algorithms to solve problems, creating many of the technical tasks we see in our everyday lives. It goes over the finer details of what exactly computer algorithms are and teaches readers how to use algorithms to perform simple tasks such as searching, sorting, and graphing. It’s a resource for anyone interested in how algorithms function in a modern world.
This is another excellent book on computer algorithms that go over a ton of algorithms with a lot of code as well. What I especially like about the book is where he actually gives examples of where he used the algorithms (or variations thereof) in practice; it really helps you see the class(es) of problems that a particular algorithm (or family of algorithms) can be used for.
The code is in C, but it’s not very esoteric and it’s easy to follow. I had also been out of school for a while and this helped me get up to speed quite quickly on a number of graph algorithms. I’ve had this book for almost 10 years now and still look at it from time to time.
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Regardless of your programming language background, Codeless Data Structures and Algorithms has you covered. In this book, author Armstrong Subero will help you learn DSAs without writing a single line of code. Straightforward explanations and diagrams give you a confident handle on the topic while ensuring you never have to open your code editor, use a compiler, or look at an integrated development environment. Subero introduces you to linear, tree, and hash data structures and gives you important insights behind the most common algorithms that you can directly apply to your own programs.
Codeless Data Structures and Algorithms provides you with the knowledge about DSAs that you will need in the professional programming world, without using any complex mathematics or irrelevant information. Whether you are a new developer seeking a basic understanding of the subject or a decision-maker wanting a grasp of algorithms to apply to your projects, this book belongs on your shelf. Quite often, a new, refreshing, and unpretentious approach to a topic are all you need to get inspired.
This book functions more as a guide for brushing up on areas you will be tested on, such as in interviews or exams or certificates, and it discusses common algorithm problems and their solutions. It covers the fundamentals of data structures and how algorithms work, as well as teaching readers how to write their own.
The material does require a familiarity with mathematics and C/C++ code to complete the exercises. At over 400 pages and 20 chapters, this book is essentially a workbook for solving algorithmic problems.
Introduction to Algorithms: A Creative Approach By Udi Manber is another great book for self-study as it is full of hundreds of problems and examples. It is designed to enhance the candidate’s problem-solving abilities and understanding of the principles behind algorithm design, which will help you to develop your Problem solving and Coding skills.
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This book highlights the importance of data structures in algorithms and optimizing searches. It’s not for the faint of heart, as it’s a graduate-level text meant for advanced readers and data science practitioners, and it delves into the complexities of data storage within data analysis.
The book covers the different data structures and variants in detail, discussing stacks, queues, hash tables, search trees, and more. It even includes more specialized structures like interval trees. The chapters include working code examples in C and references to support the work. This is a textbook for the intricacies of data storage, so expect a dense level of detail and comprehensiveness.
Another good intro book on algorithms and data structures. A lovely and clear book and any programmer who doesn’t like heavy use of Mathematics on the algorithm will appreciate this book.
Btw, if you find this book difficult to read, which is what some of my readers complain then you can also take a look at the Grokking Algorithms by Aditya Bhargava, one of the easiest and interesting books on Algorithms for beginners.
This is not really a reference or introductory manual like most books on algorithms, instead, it’s a more historical look at how algorithms have become more and more prominent in our lives, eventually automating skilled tasks previously performed by hand.
Algorithms are now assisting in driving cars, augmenting entertainment media, and predicting human behaviour. This book is more of a review and commentary to put the esoteries of algorithms into an accessible cultural context.
O’Reilly’s Algorithms, in a Nutshell, is a very good book to learn programming algorithms, especially for Java programmers. It describes the algorithms with a focus on implementing them and without heavy mathematics used in classic books on algorithms. All algorithms are presented in pattern form, with a motivation to use them, pictures and pseudo-code giving a high-level overview, and working code (in C, C++, Java, and Ruby).
They also have benchmarks to provide proofs of the theoretical performance of the algorithms. In short, one of the best book to learn algorithms for programmers.