Data structures and algorithms are the fundamentals of software development. The study of data structures and algorithms involves a lot of thinking ability and exercise of the brain. From many big tech giants like Google, Amazon, Microsoft, etc to the new emerging startups like Zomato, Swiggy, etc, all have interview rounds based on data structures and algorithms. Since Data structures and Algorithms are so important, not just for the hiring processes but also for the development of the Problem-Solving Skills of a developer, it is very important to know about the best resources to study them. This discussion focuses on some of the best books on Data structures and Algorithms.
Here we have a list of some of the best books that you can use to study data structures and algorithms go in-depth of the concepts and feel them yourself. The books are not arranged in any particular order (from best to lowest or vice versa). Think of it as 10 equal-level good books, just for different needs.
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About the book: This book is often said to be the bible for Algorithms. The book has a lot of famous algorithms ranging from a variety of topics like Dynamic Programming and greedy methods to various advanced Graph Algorithms and even Multithreaded Algorithms, algorithms related to Number Theory, and whatnot. However, this book is not that beginner-friendly but it is highly recommended in Colleges and Universities. The book is practical, with problems, diagrams, proofs, and implementations. It assumes familiarity with basic data structures and math. The book is famous by the name of CLRS Book on Algorithms.
Recommendation: Read after acquiring a good understanding of basic data structures like Arrays, Strings, Linked Lists, Stacks, and Queues and when one has a fair idea (beginner level only) about algorithms.
About the book: A beginner-friendly book that covers various beginner-level topics like introduction to Data structures and various data structures like Linked Lists, Stacks, and Queues along with some advanced and in-depth topics like Graph Algorithms, Dynamic Programming Algorithms, Greedy algorithms, and many more. The programs in this book are given in C Programming Language, making it a guide for interviews, exams, and certificates. Over 400 pages, it serves as a workbook for solving algorithmic problems, requiring familiarity with math and C/C++.
About the book: This book is one of the top recommendations for Java Programmers as it covers the basics of Data structures and algorithms in Java and goes up to a decent level. The book covers various topics like fundamentals and introduction to data structures and algorithms using Java to some advanced Graph Algorithms, String Matching Algorithms, Network Flow, Reductions, etc. It is one of the highest-rated books especially for Java programmers as there are limited high-quality books that provide in-depth knowledge of data structures and Algorithms and use Java for it.
About the book: This is an advanced-level book for programmers who already have an understanding of data structures and algorithms and are seeking an in-depth exploration of the mathematical aspects of algorithm design. Unlike other algorithm books, this one takes a creative approach to algorithmic problem-solving. The book is known for its advanced content, focusing on mathematical aspects rather than providing a hands-on guide for coding interviews. It covers a wide range of topics creatively and analytically, making it suitable for readers interested in delving into the mathematical complexities of algorithm design.
Recommendation: This book is not for beginners or those preparing for coding interviews. The book is quite advanced in its level. The fact that this book is quite advanced can be stated by a simple example that there is only 1 chapter in which all the data structures have been covered. It is highly recommended based on the user interest. If someone wants to have a deep mathematical analysis of how the algorithms are designed, this book is for you.
Recommendation: This book focuses more on Python programming and data structures in Python to be precise. It can be used by beginners currently learning Python programming to build their foundation strong by already learning some of the basic data structures in Python apart from the Language.
About the book: This is one of the best books to learn Data Structures and Algorithms for Java, C, C++, and Python Programmers. The book has implementation tips (only tips not the entire code) for all of the above-stated programming languages. Mainly, the programs are in the C programming language. The explanations are very good with proper dry-run of the algorithms using diagrams, UML diagrams are also used in many places to explain the concepts clearly. The book is divided into 4 parts which cover very basic topics like searching and sorting basic algorithms to advanced topics like Network flow algorithms, Computational Geometry, etc.
About the book: This book focuses on the importance of data structures in algorithms and optimizing searches. It is designed for advanced readers and data science practitioners, offering an in-depth exploration of data storage within data analysis. The book covers various data structures and their variants, providing detailed discussions on topics such as stacks, queues, hash tables, search trees, and more. It goes beyond basic data structures and includes discussions on specialized structures like interval trees. Throughout the book, readers can find working code examples in the C programming language, enhancing the understanding of practical implementations.
Recommendation: This book is ideal for advanced readers, especially graduate students and data science practitioners, with a deep understanding of data structures and algorithms. It delves into intricate details of data storage in the context of data analysis, making it less suitable for beginners or those seeking an introductory exploration of data structures.
Of the four books I have bought on data structures and algorithms, here are myrecommended 2.
(yes they are amazon affiliate links)
(but i have read both, multiple times, and bought the academic one 3 times)
I think algorithms and data structures, except for small syntatic differences, are language-independent. If you get a Numerical Recipes version for Fortran (or maybe even a Matlab book, that probably exists), the syntax will be similar enough so that you can adapt the examples to Julia.
Hello guys, I have read many books on data structures and algorithms like Introduction to Algorithms by Thomas H. Corman and Algorithm design manual by Steve S. Skiena, so when I come to know about this book, I thought, it's just another book on algorithms, but I was wrong.
It doesn'tcover all the data structure and algorithms you see in Computer Science but whatever it covers, it does really well and that's what matters most for beginner programmer or Computer Science students.
Let's accept it, data structure and algorithms is interesting but at the same time they are very complex and hard to understand, especially, if not explained very well and that's where this book rocks.
The book has around 400 diagrams and they are all unique (one example is below). They go nicely with the text and help you to visualize how an algorithm is working or how a data structure is working.
3. Thought to provoke use cases like when you have to design an app to keep track of your expense where you need to add and remove items more regularly and viewing it once or twice in a month, which data structure will you use?
But, if you are someone who prefers active learning like online courses then you can combine this book with Data Structures and Algorithms: Deep Dive Using Java course from Udemy, which covers a lot more data structure than Grokking Algorithm and effectively complement the book.
As contrary to many of you thinking, the book is surely not a replacement of classic titles such as Introduction to Algorithms by Thomas H. Cormen because it's not comprehensive and doesn't cover most of the data structure like Tree or Trie, etc.
At best, it's an introductory book on data structure and algorithms which makes the somewhat dry topic of data structure and algorithms more interesting. Following are some things that I missed in this book:
The book is kinda light on data structures, which is a counterpart of algorithms because algorithms work on data structure and its the choice of a data structure which affect algorithms, would have been better if Aditya provided some more content on an essential data structure like a binary tree, binary search tree, trie, etc.
Btw, if you want to explore more data structure and algorithms than given in this book, I also suggest checking out Algorithms and Data Structures by Robert Horvick, an online course from Pluralsight.
P. S. --- If you prefer online courses more than books or want the best of both worlds then you can also check the Data Structures and Algorithms: Deep Dive Using Java along with reading this book. This will help you to learn these key skills better.
F# provides you with many data structures for collections, but in functional programming, you try to have immutable data structures, such as the F# List. It becomes quite handy if you want to do some parallel computing, for example.
I would actually not bother with F# data structures for this - many of them are actually slower than ordinary .NET collections. My approach is to use SortedDictionary for bids and asks. That way, you always know the best prices on the market.
Text editors can be an interesting challenge to program. The types of problems that text editors need to solve can range from trivial to mind-bogglingly difficult. Recently, I have been on something of a spiritual journey to rework some internal data structures in an editor I have been building, specifically the most fundamental data structure to any text editor: the text. 0852c4b9a8