Open Data Structures Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Open Data Structures book. This book definitely worth reading, it is an incredibly well-written.
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.
Codeless Data Structures and Algorithms by Armstrong Subero Pdf
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 LearnUnderstand tree data structures without delving into unnecessary details or going into too much theoryGet 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 ForThis 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.
Data Structures and Algorithms: A First Course by Iain T. Adamson Pdf
All young computer scientists who aspire to write programs must learn something about algorithms and data structures. This book does exactly that. Based on lecture courses developed by the author over a number of years the book is written in an informal and friendly way specifically to appeal to students. The book is divided into four parts: the first on Data Structures introduces a variety of structures and the fundamental operations associated with them, together with descriptions of how they are implemented in Pascal; the second discusses algorithms and the notion of complexity; Part III is concerned with the description of successively more elaborate structures for the storage of records and algorithms for retrieving a record from such a structure by means of its key; and finally, Part IV consists of very full solutions to nearly all the exercises in the book.
Data Structures and Algorithm Analysis in C+ by Mark Allen Weiss Pdf
In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text. New to this Edition *An appendix on the Standard Template Library (STL) *C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard 0201361221B04062001
An Introduction to Data Structures and Algorithms by J.A. Storer Pdf
Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel
R Data Structures and Algorithms by Dr. PKS Prakash,Achyutuni Sri Krishna Rao Pdf
Increase speed and performance of your applications with efficient data structures and algorithms About This Book See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and sorting algorithms Understand important concepts such as big-o notation, dynamic programming, and functional data structured Who This Book Is For This book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected. What You Will Learn Understand the rationality behind data structures and algorithms Understand computation evaluation of a program featuring asymptotic and empirical algorithm analysis Get to know the fundamentals of arrays and linked-based data structures Analyze types of sorting algorithms Search algorithms along with hashing Understand linear and tree-based indexing Be able to implement a graph including topological sort, shortest path problem, and Prim's algorithm Understand dynamic programming (Knapsack) and randomized algorithms In Detail In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. Style and approach This easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.
Advanced Data Structures by Suman Saha,Shailendra Shukla Pdf
Advanced data structures is a core course in Computer Science which most graduate program in Computer Science, Computer Science and Engineering, and other allied engineering disciplines, offer during the first year or first semester of the curriculum. The objective of this course is to enable students to have the much-needed foundation for advanced technical skill, leading to better problem-solving in their respective disciplines. Although the course is running in almost all the technical universities for decades, major changes in the syllabus have been observed due to the recent paradigm shift of computation which is more focused on huge data and internet-based technologies. Majority of the institute has been redefined their course content of advanced data structure to fit the current need and course material heavily relies on research papers because of nonavailability of the redefined text book advanced data structure. To the best of our knowledge well-known textbook on advanced data structure provides only partial coverage of the syllabus. The book offers comprehensive coverage of the most essential topics, including: Part I details advancements on basic data structures, viz., cuckoo hashing, skip list, tango tree and Fibonacci heaps and index files. Part II details data structures of different evolving data domains like special data structures, temporal data structures, external memory data structures, distributed and streaming data structures. Part III elucidates the applications of these data structures on different areas of computer science viz, network, www, DBMS, cryptography, graphics to name a few. The concepts and techniques behind each data structure and their applications have been explained. Every chapter includes a variety of Illustrative Problems pertaining to the data structure(s) detailed, a summary of the technical content of the chapter and a list of Review Questions, to reinforce the comprehension of the concepts. The book could be used both as an introductory or an advanced-level textbook for the advanced undergraduate, graduate and research programmes which offer advanced data structures as a core or an elective course. While the book is primarily meant to serve as a course material for use in the classroom, it could be used as a starting point for the beginner researcher of a specific domain.
Data Structures and Algorithms in Java by Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser Pdf
The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich and Tomassia's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.
Open Data Exposed by Bastiaan van Loenen,Glenn Vancauwenberghe,Joep Crompvoets Pdf
The main objectives of this book are to expose key aspects that have a relevance when dealing with open data viewed from different perspectives and to provide appealing examples of how open data is implemented worldwide. The concept of open data as we know it today is the result of many different initiatives, both of a legislative and non-legislative nature, and promoted by a wide range of actors. Numerous regulatory antecedents to foster the concept of open data and embed it in national and international policy agendas have been undertaken on both sides of the Atlantic, as well as at a supranational level. The book highlights a number of the efforts made to promote open data in Europe, Asia and the United States. In addition to new insights, practical guidance and multiple disciplinary perspectives on open data, the book also addresses the transformation of current developments towards open data, which may be referred to as the democratisation of data. This book will support open data practitioners as well as open data scholars in their endeavours to promote open data implementation and research. Bastiaan van Loenen is associate professor and director of the Knowledge Centre Open Data at the Faculty of Architecture and The Built Environment of Delft University of Technology in the Netherlands, as is Glenn Vancauwenberghe, who is a post-doctoral researcher, and Joep Crompvoets is a professor at the Public Governance Institute of the KU Leuven in Belgium.
R for Data Science by Hadley Wickham,Garrett Grolemund Pdf
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Guide to Data Structures by James T. Streib,Takako Soma Pdf
This accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continuation from the material provided in the separate Springer title Guide to Java by the same authors.Topics and features: reviews the preliminary concepts, and introduces stacks and queues using arrays, along with a discussion of array-based lists; examines linked lists, the implementation of stacks and queues using references, binary trees, a range of varied sorting techniques, heaps, and hashing; presents both primitive and generic data types in each chapter, and makes use of contour diagrams to illustrate object-oriented concepts; includes chapter summaries, and asks the reader questions to help them interact with the material; contains numerous examples and illustrations, and one or more complete program in every chapter; provides exercises at the end of each chapter, as well as solutions to selected exercises, and a glossary of important terms. This clearly-written work is an ideal classroom text for a second semester course in programming using the Java programming language, in preparation for a subsequent advanced course in data structures and algorithms. The book is also eminently suitable as a self-study guide in either academe or industry.
The Design of Dynamic Data Structures by Mark H. Overmars Pdf
In numerous computer applications there is a need of storing large sets of objects in such a way that some questions about those objects can be answered efficiently. Data structures that store such sets of objects can be either static (built for a fixed set of objects) or dynamic (insertions of new objects and deletions of existing objects can be performed). Especially for more complex searching problems as they arise in such fields as computational geometry, database design and computer graphics, only static data structures are available. This book aims at remedying this lack of flexibility by providing a number of general techniques for turning static data structures for searching problems into dynamic structures. Although the approach is basically theoretical, the techniques offered are often practically applicable. The book is written in such a way that it is readable for those who have some elementary knowledge of data structures and algorithms. Although this monograph was first published in 1983, it is still unique as a general treatment of methods for constructing dynamic data structures.
Hands-On Data Structures and Algorithms with Rust by Claus Matzinger Pdf
Design and implement professional level programs by exploring modern data structures and algorithms in Rust. Key FeaturesUse data structures such as arrays, stacks, trees, lists and graphs with real-world examplesLearn the functional and reactive implementations of the traditional data structuresExplore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner.Book Description Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. What you will learnDesign and implement complex data structures in RustAnalyze, implement, and improve searching and sorting algorithms in RustCreate and use well-tested and reusable components with RustUnderstand the basics of multithreaded programming and advanced algorithm designBecome familiar with application profiling based on benchmarking and testingExplore the borrowing complexity of implementing algorithmsWho this book is for This book is for developers seeking to use Rust solutions in a practical/professional setting; who wants to learn essential Data Structures and Algorithms in Rust. It is for developers with basic Rust language knowledge, some experience in other programming languages is required.
