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Textbook of Data Structures and Algorithms, Volume 2
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
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Advanced Topics in Java
Java is one of the most widely used programming languages today. It was first released by Sun Microsystems in 1995. Over the years, its popularity has grown to the point where it plays an important role in most of our lives. From laptops to data centers, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere! There are tons of applications and heaps of websites that will not work unless you have Java installed, and more are created every day. And, of course, Java is used to power what has become the world's most dominant mobile platform, Android. Advanced Topics In Java teaches the algorithms and concepts that any budding software developer should know. You'll delve into topics such as sorting, searching, merging, recursion, random numbers and simulation, among others. You will increase the range of problems you can solve when you learn how to create and manipulate versatile and popular data structures such as binary trees and hash tables. This book assumes you have a working knowledge of basic programming concepts such as variables, constants, assignment, selection (if..else) and looping (while, for). It also assumes you are comfortable with writing functions and working with arrays. If you study this book carefully and do the exercises conscientiously, you would become a better and more agile software developer, more prepared to code today's applications - no matter the language.
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Textbook of Data Structures and Algorithms, Volume 3
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
R 5,373.00
Algorithms and Data Structures
This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 16th International Symposium on Algorithms and Data Structures, WADS, 2019, held in Edmonton, AB, Canada, in August 2019. The 42 full papers presented together with 3 invited lectures, we carefully reviewed and selected from a total of 88 submissions. They present original research on the theory and application of algorithms and data structures in many areas, including combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
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Algorithms and Data Structures
This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application.This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.
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Data Structures and Algorithms in C++: Pocket Primer
This book takes a minimalist approach to the traditional data structures course. It covers only those topics that are absolutely essential; the more esoteric structures and algorithms are left for later study. Suitable for an introductory data structures course or self-study, this book is written from the ground up in C++ (not translated from a Java-based text), and uses features of the C++ Standard Template Library to illustrate important concepts. A unique feature of the text is its use of literate programming techniques (originally developed by Donald Knuth) to present the sample code in a way that keeps the code from overwhelming the accompanying explanations. This book is suitable for an undergraduate data structures course using C++ or for developers needing review.Features:Takes a ""minimalist"" approach to the material that presents only essential concepts. This enables readers to focus on (and remember) just what they'll need.Uses select features of the C++11 standard to simplify the sample code and make it easier to understand.Connects the concepts directly to the classes provided the Standard Template Library (STL), and shows how these classes can be implemented in C++. Uses ""literate programming"" techniques that allow the presentation of the sample code to more clearly show the details of the code as well as how the pieces fit together.
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Data Structures and Algorithms Using C#
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.
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Common-Sense Guide to Data Structures and Algorithms in Javascript, Volume 1
If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your JavaScript 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. Every chapter features practice exercises to give you the hands-on information 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. The JavaScript edition uses JavaScript exclusively for all code examples, exercises, and solutions. 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 JavaScript code faster and more scalable. What You Need: Certain code examples take advantage of recently introduced JavaScript features. Therefore, it's important to use a JavaScript environment that supports ECMAScript 6+ or a newer version.
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Data Structures and Algorithms Using C#
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.
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 17th International Symposium on Algorithms and Data Structures, WADS 2021, held in virtually in August 2021. The 47 full papers, presented together with two invited lectures, were carefully reviewed and selected from a total of 123 submissions. They present original research on the theory, design and application of algorithms and data structures.
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Hands-On Data Structures and Algorithms with Kotlin
Understand and solve complex computational problems and write efficient code with KotlinKey FeaturesLearn about important data structures such as lists, arrays, queues, and stacksDesign custom algorithms for real-life implementationsIdentify suitable tools for different scenarios and deliver immediate resultsBook DescriptionData structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory.Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally.By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems.What you will learnUnderstand the basic principles of algorithms and data structuresExplore general-purpose data structures with arrays and linked listsGet to grips with the basics of stacks, queues, and double-ended queuesUnderstand functional programming and related data structuresUse performant searching and efficient sortingUncover how Kotlin's collection framework functionsBecome adept at implementing different types of mapsWho this book is forIf you're a Kotlin developer who wants to learn the intricacies of implementing data structures and algorithms for scalable application development, this book is for you.
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Data Structures, Algorithms, and Invariants
Data Structures, Algorithms, and Invariants: A Practical Guide provides students with the knowledge and understanding they need to make sensible decisions regarding the choice of an abstract data type (ADT) for particular use cases. The book is a practical guide that helps readers with the process of building a software application utilizing a variety of list-based, tree-based, and graph-based ADTs.The opening chapters discuss solving problems, the concept of computational complexity, different types of ADTs, and why they are needed in software development. Additional chapters address unordered, positional, and ordered ADTs, the process of sorting, ways of determining order, and graphs. Each chapter features an introduction, learning objectives, key terms, takeaways, QR codes that link out to additional content such as videos, and chapter review questions to support the reading and learning experience. Additionally, students gain access to a companion source code repository that provides implementations of many of the ADTs.Data Structures, Algorithms, and Invariants is an ideal textbook for data structure and algorithms courses in information science, data science, and programming.
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Schaum's Outline of Data Structures with Java, 2ed
Tough Test Questions? Missed Lectures? Not Enough Time?Fortunately for you, there's Schaum's Outlines. More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills. This Schaum's Outline gives youPractice problems with full explanations that reinforce knowledgeCoverage of the most up-to-date developments in your course fieldIn-depth review of practices and applicationsFully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum's to shorten your study time-and get your best test scores!Schaum's Outlines-Problem Solved.
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Algorithms and Data Structures
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java.The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
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Data Structures and Algorithms: A First Course
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.
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Common-Sense Guide to Data Structures and Algorithms, 2e
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
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Algorithms and Data Structures
This book contains the papers presented at the 1989 Workshop on Algorithms and Data Structures, which succeeds the 1988 Scandinavian Workshop on Algorithm Theory. It presents current research in various areas of algorithms, computational geometry, geometric searching, VLSI placement and routing, graph algorithms, parallel algorithms, distributed algorithms, databases, and text searching.
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Algorithms and Data Structures
With numerous practical, real-world algorithms presented in the C programming language, Bowman's Algorithms and Data Structures: An Approach in C is the algorithms text for courses that take a modern approach. For the one- or two-semester undergraduate course in data structures, it instructs students on the science of developing and analysing algorithms. Bowman focuses on both the theoretical and practical aspects of algorithm development. He discusses problem-solving techniques and introduces the concepts of data abstraction and algorithm efficiency. More importantly, the text does not present algorithms in a "shopping-list" format. Rather it provides actual insight into the design process itself
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 10th International Workshop on Algorithms and Data Structures, WADS 2007, held in Halifax, Canada, in August 2007. The papers present original research on the theory and application of algorithms and data structures in all areas, including combinatorics, computational geometry, databases, graphics, parallel and distributed computing.
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Data Structures and Algorithms with Scala
This practically-focused textbook presents a concise tutorial on data structures and algorithms using the object-functional language Scala. The material builds upon the foundation established in the title Programming with Scala: Language Exploration by the same author, which can be treated as a companion text for those less familiar with Scala.Topics and features: discusses data structures and algorithms in the form of design patterns; covers key topics on arrays, lists, stacks, queues, hash tables, binary trees, sorting, searching, and graphs; describes examples of complete and running applications for each topic; presents a functional approach to implementations for data structures and algorithms (excepting arrays); provides numerous challenge exercises (with solutions), encouraging the reader to take existing solutions and improve upon them; offers insights from the author’s extensive industrial experience; includes a glossary, and an appendix supplying an overview of discrete mathematics.Highlighting the techniques and skills necessary to quickly derive solutions to applied problems, this accessible text will prove invaluable to time-pressured students and professional software engineers.
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Algorithms and Data Structures
The papers in this volume were presented at the Seventh Workshop on Al- rithms and Data Structures (WADS 2001). The workshop took place August 8-10, 2001 in Providence, Rhode Island, USA. The workshop alternates with the Scandinavian Workshop on Algorithms Theory (SWAT), continuing the t- dition of SWAT and WADS starting with SWAT '88 and WADS '89. In response to the call for papers, 89 papers were submitted. From these submissions, the program committee selected 40 papers for presentation at the workshop. In addition invited plenary lectures were given by the following - stinguished researchers: Mikhail J. Atallah, F. Thomson Leighton, and Mihalis Yannakakis. On behalf of the program committee, we would like to express our apprec- tion to the invited speakers and to all the authors who submitted papers. August 2001 Frank Dehne J.. org-Rudiger .. Sack Roberto Tamassia Organization Conference Chair Roberto Tamassia (Brown) Program Committee Chairs Frank Dehne (Carleton) J.. org-Rudiger .. Sack (Carleton) Roberto Tamassia (Brown) Program Committee Alberto Apostolico (Purdue, Padova) Giuseppe Liotta (Perugia) Timothy Chan (Waterloo) Ernst W. Mayr (Munc .. hen) Bruno Codenotti (IMC) Joseph S.B. Mitchell (SUNY) Giuseppe Di Battista (Roma Tre) Stefan N.. aher (Trier) Shlomi Dolev (Ben-Gurion) Takao Nishizeki (Tohoku) Martin Farach-Colton Viktor K. Prasanna (USC) (Rutgers, Google) Enrico Puppo (Genova) Pierre Fraigniaud (LRI) Jose Rolim (Geneva) Harold N. Gabow (Colorado) Jack Snoeyink (UNC) Sally A. Goldman (Washington) Ioannis G. Tollis (UTD) Michael T.
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Algorithms and Data Structures
The papers in this volume were presented at the Sixth Workshop on Algorithms and Data Structures (WADS '99). The workshop took place August 11 - 14, 1999, in Vancouver, Canada. The workshop alternates with the Scandinavian Workshop on Algorithms Theory (SWAT), continuing the tradition of SWAT and WADS starting with SWAT'88 and WADS'89. In response to the program committee's call for papers, 71 papers were submitted. From these submissions, the program committee selected 32 papers for presentation at the workshop. In addition to these submitted papers, the program committee invited the following researchers to give plenary lectures at the workshop: C. Leiserson, N. Magnenat-Thalmann, M. Snir, U. Vazarani, and 1. Vitter. On behalf of the program committee, we would like to express our appreciation to the six plenary lecturers who accepted our invitation to speak, to all the authors who submitted papers to W ADS'99, and to the Pacific Institute for Mathematical Sciences for their sponsorship. Finally, we would like to express our gratitude to all the people who reviewed papers at the request of the program committee. August 1999 F. Dehne A. Gupta J.-R. Sack R. Tamassia VI Conference Chair: A. Gupta Program Committee Chairs: F. Dehne, A. Gupta, J.-R. Sack, R. Tamassia Program Committee: A. Andersson, A. Apostolico, G. Ausiello, G. Bilardi, K. Clarkson, R. Cleve, M. Cosnard, L. Devroye, P. Dymond, M. Farach-Colton, P. Fraigniaud, M. Goodrich, A.
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Textbook of Data Structures and Algorithms, Volume 1
Data structures and algorithms is a fundamental course in Computer Science, which enables learners across any discipline to develop the much-needed foundation of efficient programming, leading to better problem solving in their respective disciplines. A Textbook of Data Structures and Algorithms is a textbook that can be used as course material in classrooms, or as self-learning material. The book targets novice learners aspiring to acquire advanced knowledge of the topic. Therefore, the content of the book has been pragmatically structured across three volumes and kept comprehensive enough to help them in their progression from novice to expert. With this in mind, the book details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language. It includes 181 illustrative problems and 276 review questions to reinforce a theoretical understanding and presents a suggestive list of 108 programming assignments to aid in the implementation of the methods covered.
R 5,373.00
Hands-On Data Structures and Algorithms with Python
Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficientKey FeaturesExplore functional and reactive implementations of traditional and advanced data structuresApply a diverse range of algorithms in your Python codeImplement the skills you have learned to maximize the performance of your applicationsBook DescriptionChoosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.What you will learnUnderstand common data structures and algorithms using examples, diagrams, and exercisesExplore how more complex structures, such as priority queues and heaps, can benefit your codeImplement searching, sorting, and selection algorithms on number and string sequencesBecome confident with key string-matching algorithmsUnderstand algorithmic paradigms and apply dynamic programming techniquesUse asymptotic notation to analyze algorithm performance with regard to time and space complexitiesWrite powerful, robust code using the latest features of PythonWho this book is forThis book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.
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