20 Best Book For Data Structures (Jan 2023 Update)

If you thought that data structures and algorithms were all just theory, you're missing out on what they can do for your code. learn to use big o notation to make your code run faster by orders of magnitude. choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. with simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. this new edition features practice exercises in every chapter, and new chapters on topics such as dynamic programming and heaps and tries. get the hands-on info you need to master data structures and algorithms for your day-to-day work. 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. take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code, with examples in javascript, python, and ruby. this new and revised second edition features new chapters on recursion, dynamic programming, and using big o in your daily work. use big o notation 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. practice your new skills with exercises in every chapter, along with detailed solutions. use these techniques today to make your code faster and more scalable.

With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. it uses microsoft c++ as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. the text also explores tradeoff issues, familiarizes readers with the most commonly used data structures and their algorithms, and discusses matching appropriate data structures to applications. the author offers explicit coverage of design patterns encountered in the course of programming the book's basic data structures and algorithms. numerous examples appear throughout the text.

A book with obvious wear. may have some damage to the cover or binding but integrity is still intact. there might be writing in the margins possibly underlining and highlighting of text but no missing pages or anything that would compromise the legibility or understanding of the text.

The authors' treatment of data structures in data structures and algorithms is unified by an informal notion of "abstract data types," allowing readers to compare different implementations of the same concept. algorithm design techniques are also stressed and basic algorithm analysis is covered. most of the programs are written in pascal.

Data structures and algorithm analysis in java is an “advanced algorithms” book that fits between traditional cs2 and algorithms analysis courses. in the old acm curriculum guidelines, this course was known as cs7. this text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math. as the speed and power of computers increases, so does the need for effective programming and algorithm analysis. by approaching these skills in tandem, mark allen weiss teaches readers to develop well-constructed, maximally efficient programs in java. weiss clearly explains topics from binary heaps to sorting to np-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. figures and examples illustrating successive stages of algorithms contribute to weiss' careful, rigorous and in-depth analysis of each type of algorithm. a logical organization of topics and full access to source code complement the text's coverage.

In the era of self-taught developers and programmers, essential topics in the industry are frequently learned without a formal academic foundation. a solid grasp of data structures and algorithms (dsa) is imperative for anyone looking to do professional software development and engineering, but classes in the subject can be dry or spend too much time on theory and unnecessary readings. 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 is all you need to get inspired. what you'll learn – understand tree data structures without delving into unnecessary details or going into too much theory – get started learning linear data structures with a basic discussion on computer memory study an overview of arrays, linked lists, stacks and queues – who this book is for – this book is for beginners, self-taught developers and programmers, and anyone who wants to understand data structures and algorithms but don’t want to wade through unnecessary details about quirks of a programming language or don’t have time to sit and read a massive book on the subject. this book is also useful for non-technical decision-makers who are curious about how algorithms work.

If you're a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering–data structures and algorithms–in a way that's clearer, more concise, and more engaging than other materials. by emphasizing practical knowledge and skills over theory, author allen downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. you'll explore the important classes in the java collections framework (jcf), how they're implemented, and how they're expected to perform. each chapter presents hands-on exercises supported by test code online. use data structures such as lists and maps, and understand how they work build an application that reads wikipedia pages, parses the contents, and navigates the resulting data tree analyze code to predict how fast it will run and how much memory it will require write classes that implement the map interface, using a hash table and binary search tree build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results other books by allen downey include think java, think python, think stats, and think bayes.

76899-4 object-oriented programming and powerful features of c++ enable this carefully crafted text to build data structures from basic ideas into complete, fully-developed programs and interesting applications. in the process, the text explores problem solving and programming principles, data abstraction, recursion, and the comparative analysis of algorithms as fundamentals tools of software design. employing substantial case studies, reusable software development, and programming projects to increase understanding, successful authors robert l. kruse and alexander j.ryba include topics such as: c++ templates are introduced early; code for data structures is developed as templated classes in fully reusable form; the standard template library (stl) is mentioned as appropriate. recursion is treated early and applied throughout the text. data abstraction and abstract data types (adts) are emphasized, with conceptual development separated from implementation issues. advanced structures and algorithms are developed into complete programs, including splay trees, b-trees, red-black trees, and graph algorithms such as minimal spanning trees. data structures and program design in c++ will prove useful to both computer science students and professionals. the authors supply all code in this book on the web, and, as well, they provide an excellent instructor support package that includes an instructor's resource manual with transparency masters, solutions, and source code to all of the programming examples and projects in the text.

This innovative new book encourages readers to utilize the “outside-in” approach to learning the use, design and implementation of data structures. the author introduces every data structure by first narrating its properties and use in applications (the "outside" view). this provides a clear introduction to data structures with realistic context where it is used. venugopal then details how to build data structures (the "inside" view); readers learn how to evaluate usability, flexibility, extensibility, and performance in designing and implementing classic data structures.

It can be used as a reference manual by those readers in the computer science industry. the book has around 21 chapters and covers recursion and backtracking, linked lists, stacks, queues, trees, priority queue and heaps, disjoint sets adt, graph algorithms, sorting, searching, selection algorithms [medians], symbol tables, hashing, string algorithms, algorithms design techniques, greedy algorithms, divide and conquer algorithms, dynamic programming, complexity classes, and other miscellaneous concepts. this book serves as guide to prepare for interviews, exams, and campus work. it is also available in c/c++. in short, this book offers solutions to various complex data structures and algorithmic problems. – campus preparation – degree/masters course preparationinstructor'sbig job hunters: microsoft, google, apple, amazon, yahoo, flip kart, adobe, ibm labs, citrix, mentor graphics, net – app, oracle, face book, mc – afee and many more – reference manual for working people what is unique? our main objective isn't to propose theorems and proofs about ds and algorithms. that is, each problem corresponds to multiple solutions with different complexities. topics covered: introduction – recursion and backtracking – linked listsstacksqueuestreespriority queue and heaps – disjoint sets adtgraph algorithms – sorting searching selection algorithms [medians] symbol tables hashing string algorithms algorithms design techniques greedy algorithms divide and conquer algorithms dynamic programming complexity classes miscellaneous concepts target audience? these books prepare readers for interviews, exams, and campus work. language? all code was written in java. if you are using c/c++, please search for "data structures and algorithms made easy".

"many of you have provided feedback on earlier editions of this book, and your comments and suggestions have greatly improved the book. this edition has been substantially enhanced in presentation, organization, examples, exercises, and supplements.the book is fundamentals first by introducing basic programming concepts and techniques before designing custom classes. the fundamental concepts and techniques of selection statements, loops, methods, and arrays are the foundation for programming. building this strong foundation prepares students to learn object-oriented programming and advanced java programming. this book teaches programming in a problem-driven way that focuses on problem solving rather than syntax. the central thread of early chapters is on problem solving. appropriate syntax and library are introduced to enable readers to write programs forsolving the problems. to support the teaching of programming in a problem-driven way, the book provides a wide variety of problems at various levels of difficulty to motivate students. to appeal to students in all majors, the problems cover many application areas, including math, science, business, financial, gaming, animation, and multimedia. the book seamlessly integrates programming, data structures, and algorithms into one text. it employs a practical approach to teach data structures. through implementation, students gain a deep understanding on the efficiency of data structures and on how and when to use certain data structures. the book is widely used in the introductory programming, data structures, and algorithms courses in the universities around the world. this comprehensive version covers fundamentals of programming, object-oriented programming, gui programming, data structures, algorithms, concurrency, networking, database, and web programming. it is designed to prepare students to become proficient java programmers. a brief version (introduction to java programming, brief version, eleventh edition) is available for a first course on programming, commonly known as cs1. the brief version contains the first 18 chapters of the comprehensive version. an ap version of the book is also available for high school students taking an ap computer science course. the best way to teach programming is by example, and the only way to learn programming is by doing. basic concepts are explained by example and a large number of exercises with various levels of difficulty are provided for students to practice. our goal is to produce a text that teaches problem solving and programming in a broad context using a wide variety of interesting examples. if you have any comments on and suggestions for improving the book, please email me"–

Peeling data structures and algorithms for interviews [re-printed with corrections and new problems]: "data structures and algorithms made easy: data structure and algorithmic puzzles" is a book that offers solutions to complex data structures and algorithms. there are multiple solutions for each problem and the book is coded in c/c++, it comes handy as an interview and exam guide for computer scientists. – a handy guide of sorts for any computer science professional, data structures and algorithms made easy: data structure and algorithmic puzzles is a solution bank for various complex problems related to data structures and algorithms. it can be used as a reference manual by those readers in the computer science industry. the book has around 21 chapters and covers recursion and backtracking, linked lists, stacks, queues, trees, priority queue and heaps, disjoint sets adt, graph algorithms, sorting, searching, selection algorithms [medians], symbol tables, hashing, string algorithms, algorithms design techniques, greedy algorithms, divide and conquer algorithms, dynamic programming, complexity classes, and other miscellaneous concepts. data structures and algorithms made easy: data structure and algorithmic puzzles by narasimha karumanchi was published in march, and it is coded in c/c++ language. this book serves as guide to prepare for interviews, exams, and campus work. it is also available in java. in short, this book offers solutions to various complex data structures and algorithmic problems. – what is unique? our main objective isn't to propose theorems and proofs about ds and algorithms. that is, each problem corresponds to multiple solutions with different complexities. topics covered: introduction – recursion and backtracking – linked listsstacksqueuestreespriority queue and heaps – disjoint sets adtgraph algorithms – sorting searching selection algorithms [medians] symbol tables hashing string algorithms algorithms design techniques greedy algorithms divide and conquer algorithms dynamic programming complexity classes miscellaneous concepts target audience? these books prepare readers for interviews, exams, and campus work. language? all code was written in c/c++. if you are using java, please search for "data structures and algorithms made easy in java".

Mark allen weiss' innovative approach to algorithms and data structures teaches the simultaneous development of sound analytical and programming skills for the advanced data structures course. readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded. the c++ language is brought up-to-date and simplified, and the standard template library is now fully incorporated throughout the text. this third edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the fibonacci heap. known for its clear and friendly writing style, data structures and algorithm analysis in c++ is logically organized to cover advanced data structures topics from binary heaps to sorting to np-completeness. figures and examples illustrating successive stages of algorithms contribute to weiss' careful, rigorous and in-depth analysis of each type of algorithm.

Massive modern datasets make traditional data structures and algorithms grind to a halt. this fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets.in algorithms and data structures for massive datasets you will learn: probabilistic sketching data structures for practical problems choosing the right database engine for your application evaluating and designing efficient on-disk data structures and algorithms understanding the algorithmic trade-offs involved in massive-scale systems deriving basic statistics from streaming data correctly sampling streaming data computing percentiles with limited space resources algorithms and data structures for massive datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. you’ll explore the novel data structures and algorithms that underpin google, facebook, and other enterprise applications that work with truly massive amounts of data. these effective techniques can be applied to any discipline, from finance to text analysis. graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. purchase of the print book includes a free ebook in pdf, kindle, and epub formats from manning publications. about the technology standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. this unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. about the book algorithms and data structures for massive datasets introduces processing and analytics techniques for large distributed data. packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. you’ll explore real-world examples as you learn to map powerful algorithms like bloom filters, count-min sketch, hyperloglog, and lsm-trees to your own use cases. what's inside probabilistic sketching data structures choosing the right database engine designing efficient on-disk data structures and algorithms algorithmic tradeoffs in massive-scale systems computing percentiles with limited space resources about the reader examples in python, r, and pseudocode. about the author dzejla medjedovic earned her phd in the applied algorithms lab at stony brook university, new york. emin tahirovic earned his phd in biostatistics from university of pennsylvania. illustrator ines dedovic earned her phd at the institute for imaging and computer vision at rwth aachen university, germany. table of contents 1 introduction part 1 hash-based sketches 2 review of hash tables and modern hashing 3 approximate membership: bloom and quotient filters 4 frequency estimation and count-min sketch 5 cardinality estimation and hyperloglog part 2 real-time analytics 6 streaming data: bringing everything together 7 sampling from data streams 8 approximate quantiles on data streams part 3 data structures for databases and external memory algorithms 9 introducing the external memory model 10 data structures for databases: b-trees, bε-trees, and lsm-trees 11 external memory sorting

Don't simply show your data—tell a story with it! storytelling with data teaches you the fundamentals of data visualization and how to communicate effectively with data. you'll discover the power of storytelling and the way to make data a pivotal point in your story. the lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. this book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. specifically, you'll learn how to: understand the importance of context and audience determine the appropriate type of graph for your situation recognize and eliminate the clutter clouding your information direct your audience's attention to the most important parts of your data think like a designer and utilize concepts of design in data visualization leverage the power of storytelling to help your message resonate with your audience together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. rid your world of ineffective graphs, one exploding 3d pie chart at a time. there is a story in your data—storytelling with data will give you the skills and power to tell it!

Chapter 7: dictionaries and hashes; dictionaries; creating a dictionary; the has and set methods; the remove method; the get and values methods; the clear, size, keys, and getitems methods; using the dictionary class; the hash table; creating a hash table; using the hashtable class; hash table versus hash set; handling collisions between hash tables; separate chaining; linear probing; creating better hash functions; summary; chapter 8: trees; trees terminology; binary tree and binary search tree; creating the binarysearchtree class; inserting a key in a tree; tree traversal.

Provide a step-by-step introduction to programming in java starting out with java: from control structures through data structures provides a step-by-step introduction to programming in java. this text is designed to be used in a 2 or 3 semester sequence and covers everything from the fundamentals of java programming to algorithms and data structures. as with all gaddis texts, every chapter contains clear and easy-to-read code listings, concise and practical real-world examples, and an abundance of exercises. with the 4th edition, javafx has replaced swing as the standard gui library for java in chapters that focus on gui development. the swing and applet material from the previous edition is available online.

Data structures and other objects using java is a gradual, "just-in-time" introduction to data structures for a cs2 course. each chapter provides a review of the key aspects of object-oriented programming and a syntax review, giving students the foundation for understanding significant programming concepts. with this framework they are able to accomplish writing functional data structures by using a five-step method for working with data types; understanding the data type abstractly, writing a specification, using the data type, designing and implementing the data type, and analyzing the implementation. students learn to think analytically about the efficiency and efficacy of design while gaining exposure to useful java classes libraries. the flexibility of data structures and other objects using java allows instructors to structure their course around a certain emphasis, such as early coverage of recursion and sorting, or to accelerate the pace of the course.

C# programmers: no more translating data structures from c++ or java to use in your programs! mike mcmillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for c# implementation of data structures and algorithms found in the . net framework library, as well as those developed by the programmer. the approach is very practical, using timing tests rather than big o notation to analyze the efficiency of an approach. coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. this is the perfect resource for c# professionals and students alike.

Data structures and problem solving using java takes a practical and unique approach to data structures that separates interface from implementation. it is suitable for the second or third programming course. this book provides a practical introduction to data structures with an emphasis on abstract thinking and problem solving, as well as the use of java. it does this through what remains a unique approach that clearly separates each data structure's interface (how to use a data structure) from its implementation (how to actually program that structure). parts i (tour of java), ii (algorithms and building blocks), and iii (applications) lay the groundwork by discussing basic concepts and tools and providing some practical examples, while part iv (implementations) focuses on implementation of data structures. this forces the reader to think about the functionality of the data structures before the hash table is implemented. the fourth edition features many new updates as well as new exercises.