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Data Structures and Algorithms
This textbook provides an in depth course on data structures in the context of object oriented development. Its main themes are abstraction, implementation, encapsulation, and measurement: that is, that the software process begins with abstraction of data types, which then lead to alternate representations and encapsulation, and finally to resource measurement. A clear object oriented approach, making use of Booch components, will provide readers with a useful library of data structure components and experience in software reuse. Students using this book are expected to have a reasonable understanding of the basic logical structures such as stacks and queues. Throughout, Ada 95 is used and the author takes full advantage of Ada's encapsulation features and the ability to present specifications without implementational details. Ada code is supported by two suites available over the World Wide Web.
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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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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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Data Structures And Algorithms In Javascript
For Javascript developers, this book is a one-stop-shop for learning the algorithms and data structures that solve and optimize complex problems. Covering everything from functional programming and abstract data types, to sorting and searching, lists, bags, binary trees, forests, heaps, and graphs - the author uses examples taken from coding challenges and interview questions, enabling readers to explore the real-world advantages of specific algorithms and data structures. Written and illustrated to be a developer's go-to reference manual as well as for immediate on-the-job applications, performance - both from a theoretical point of view and a practical standpoint - is considered alongside every algorithm or data structure introduced. In addition to demonstrating best practices throughout the text, each chapter ends with a series of questions that amplify the preceding concepts and provide further examples for the reader to apply. Also of note, the book utilizes the latest version of
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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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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
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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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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Fabulous Adventures in Data Structures and Algorithms
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book. There's a lot more to algorithms than the useful-but-boring recipes you recite for every interview. This unique book introduces a collection of amazing algorithms that have the potential to change the way you program. In this book, language designer and C# legend Eric Lippert explores exciting, esoteric, and exotic data structures and algorithms that will expand your programming toolbox and your horizons. You'll upend the way you think about lists, learn the algorithms behind powerful developer tools, and rethink how to handle stochastic quantities in modern programming languages. Fabulous Adventures in Data Structures and Algorithms shows you how to: Build efficient, double-ended queues from immutable partsAuto-format structured text so it always looks sharpGenerate and manipulate random numbers from custom distributions using the same tools you use for sequencesHarness immutability to squeeze data smaller while speeding up repeated computationsUncover the mathematical structures underlying lists, nullables, functions, tasks, and probabilitiesAbout the book Fabulous Adventures in Data Structures and Algorithms teaches you how to solve programming challenges with lesser-known algorithmic approaches. You'll begin by examining immutable data structures--stacks, queues, deques, and unusual constructions like Hughes lists--that take on conventional assumptions about performance. Next, you'll investigate algorithms drawn from building developer tools, from backtracking search in graph coloring to unification and anti-unification. Finally, you'll venture into randomness, developing data structures and algorithms for discrete and continuous distributions, sequence operations on probability distributions, and Bayesian reasoning. About the reader For working programmers who know C#, Java, Python, or similar object-oriented language. Examples in C#. About the author Eric Lippert designed programming languages, compilers, and other developer tools for Microsoft, Coverity, and Facebook. He's been on the design and/or implementation and/or specification teams for Visual Basic, JavaScript, VBScript, C#, Hack, and Bean Machine. Eric's popular blog about language design, data structures and algorithms, and other "fabulous adventures in coding," which you can read at ericlippert.com, has enjoyed a twenty-year run.
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Functional Data Structures and Algorithms
This book is an introduction to data structures and algorithms for functional programming languages, with a focus on proofs. Starting with sorting and searching, it moves on to priority queues and advanced design and analysis techniques: dynamic programming, amortized analysis, splay trees, skew heaps and pairing heaps. The final part of the book covers a number of selected fun topics: graph algorithms, string search, Huffman's algorithm for generating optimal codes and alpha-beta pruning of game trees. The book covers both correctness (does the algorithm do what it is supposed to do?) and running time analysis (does the algorithm terminate within a specified number of steps?). It does so in a unified manner with inductive proofs about functional programs and their running time functions. What sets this book apart from existing books on algorithms is that all proofs have been machine-checked, by the proof assistant Isabelle. That is, in addition to the text in the book, which requires no knowledge of proof assistants!, the Isabelle definitions and proofs are available online. The structured nature of Isabelle proofs permits even novices to follow the high-level arguments. This book is aimed at teachers and students (it has been classroom-tested for a number of years) but is also a reference work for programmers and researchers who are interested in the (verified!) details of some algorithm or proof.
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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.
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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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Essential Algorithms
A friendly introduction to the most useful algorithms written in simple, intuitive English The revised and updated second edition of Essential Algorithms, offers an accessible introduction to computer algorithms. The book contains a description of important classical algorithms and explains when each is appropriate. The author shows how to analyze algorithms in order to understand their behavior and teaches techniques that the can be used to create new algorithms to meet future needs. The text includes useful algorithms such as: methods for manipulating common data structures, advanced data structures, network algorithms, and numerical algorithms. It also offers a variety of general problem-solving techniques. In addition to describing algorithms and approaches, the author offers details on how to analyze the performance of algorithms. The book is filled with exercises that can be used to explore ways to modify the algorithms in order to apply them to new situations. This updated edition of Essential Algorithms: Contains explanations of algorithms in simple terms, rather than complicated mathSteps through powerful algorithms that can be used to solve difficult programming problemsHelps prepare for programming job interviews that typically include algorithmic questionsOffers methods can be applied to any programming languageIncludes exercises and solutions useful to both professionals and studentsProvides code examples updated and written in Python and C# Essential Algorithms has been updated and revised and offers professionals and students a hands-on guide to analyzing algorithms as well as the techniques and applications. The book also includes a collection of questions that may appear in a job interview. The book’s website will include reference implementations in Python and C# (which can be easily applied to Java and C++).
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Codeless Data Structures and Algorithms
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 queuesWho 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.
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Hands-On Data Structures and Algorithms with Rust
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 DescriptionRust 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 forThis 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.
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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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Functional Data Structures and Algorithms
This book is an introduction to data structures and algorithms for functional programming languages, with a focus on proofs. Starting with sorting and searching, it moves on to priority queues and advanced design and analysis techniques: dynamic programming, amortized analysis, splay trees, skew heaps and pairing heaps. The final part of the book covers a number of selected fun topics: graph algorithms, string search, Huffman's algorithm for generating optimal codes and alpha-beta pruning of game trees. The book covers both correctness (does the algorithm do what it is supposed to do?) and running time analysis (does the algorithm terminate within a specified number of steps?). It does so in a unified manner with inductive proofs about functional programs and their running time functions. What sets this book apart from existing books on algorithms is that all proofs have been machine-checked, by the proof assistant Isabelle. That is, in addition to the text in the book, which requires no knowledge of proof assistants!, the Isabelle definitions and proofs are available online. The structured nature of Isabelle proofs permits even novices to follow the high-level arguments. This book is aimed at teachers and students (it has been classroom-tested for a number of years) but is also a reference work for programmers and researchers who are interested in the (verified!) details of some algorithm or proof.
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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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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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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 15th Algorithms and Data Structures Symposium, WADS 2017, held in St. John's, NL, Canada, in July/August 2017. The 49 full papers presented together with 3 abstracts of invited talks were carefully reviewed and selected from 109 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.The WADS Symposium, which alternates with the Scandinavian Symposium and Workshops on Algorithm Theory, SWAT, is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. Papers presenting original research on the theory and application of algorithms and data structures
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 14th Algorithms and Data Structures Symposium, WADS 2015, held in Victoria, BC, Canada, August 2015. The 54 revised full papers presented in this volume were carefully reviewed and selected from 148 submissions. The Algorithms and Data Structures Symposium - WADS (formerly Workshop on Algorithms And Data Structures), which alternates with the Scandinavian Workshop on Algorithm Theory, is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. WADS includes papers presenting original research on algorithms and data structures in all areas, including bioinformatics, combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
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Hands-On Data Structures and Algorithms with Python
Learn to implement complex data structures and algorithms using PythonKey FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook DescriptionData structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.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. You will get insights into Python implementation of all the important and relevant algorithms.What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is forThis book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
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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
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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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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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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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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