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Composite Data Structures and Modularization
This book covers C-Programming focussing on its practical side. Volume 2 deals mainly with composite data structures and their composition. An extensive use of figures and examples help to give a clear description of concepts and help the reader to gain a systematic understanding of the programming language.
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Advanced Data Structures
This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.
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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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Advanced Data Structures
This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.
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Data Structures
This text is intended for the one-term course in data structures with the following prerequisites: mastery of a high-level programming language, preferably Pascal, and finite or discrete mathematics. Each basic concept is introduced first through numerous examples and followed by advanced material allowing maximum flexibility in structuring the course. Through the use of data structures, the author has included coverage of the following related topics: recursion, pattern recognition, and dynamic programming. Extensive examples, over 300 exercises, 400 figures and tables, and 80 working algorithms contribute to student learning.
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C# Data Structures and Algorithms
Write sophisticated C# code with this complete guide to using diverse data structures and algorithms, featuring ready-to-use code snippets, detailed explanations, and illustrationsKey FeaturesMaster lists, stacks, queues, dictionaries, sets, and trees, among other data structuresDelve into effective design and implementation techniques to meet your software requirementsVisualize data structures and algorithms through illustrations for a clearer understanding of their analysisPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionBuilding your own applications is exciting but challenging, especially when tackling complex problems tied to advanced data structures and algorithms. This endeavor demands profound knowledge of the programming language as well as data structures and algorithms – precisely what this book offers to C# developers.Starting with an introduction to algorithms, this book gradually immerses you in the world of arrays, lists, stacks, queues, dictionaries, and sets. Real-world examples, enriched with code snippets and illustrations, provide a practical understanding of these concepts. You’ll also learn how to sort arrays using various algorithms, setting a solid foundation for your programming expertise. As you progress through the book, you’ll venture into more complex data structures – trees and graphs – and discover algorithms for tasks such as determining the shortest path in a graph before advancing to see various algorithms in action, such as solving Sudoku.By the end of the book, you’ll have learned how to use the C# language to build algorithmic components that are not only easy to understand and debug but also seamlessly applicable in various applications, spanning web and mobile platforms.What you will learnUnderstand the fundamentals of algorithms and their classificationStore data using arrays and lists, and explore various ways to sort arraysBuild enhanced applications with stacks, queues, hashtables, dictionaries, and setsCreate efficient applications with tree-related algorithms, such as for searching in a binary search treeBoost solution efficiency with graphs, including finding the shortest path in the graphImplement algorithms solving Tower of Hanoi and Sudoku games, generating fractals, and even guessing the title of this bookWho this book is forThis book is for developers looking to learn data structures and algorithms in C#. While basic programming skills and C# knowledge is useful, beginners will find value in the provided code snippets, illustrations, and detailed explanations, enhancing their programming skills. Advanced developers can use this book as a valuable resource for reusable code snippets, instead of writing algorithms from scratch each time.
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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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Purely Functional Data Structures
Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs can easily be adapted to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.
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Purely Functional Data Structures
Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs can easily be adapted to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.
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Data Structures and Algorithms with the C++ STL
Explore the C++ STL with practical guidance on vectors, algorithms, and custom types for intermediate developers, enriched by real-world examples.Key FeaturesMaster the std::vector and understand why it should be your default container of choiceUnderstand each STL algorithm and its practical applicationsGain insights into advanced topics such as exception guarantees and thread safetyPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWhile the Standard Template Library (STL) offers a rich set of tools for data structures and algorithms, navigating its intricacies can be daunting for intermediate C++ developers without expert guidance. This book offers a thorough exploration of the STL’s components, covering fundamental data structures, advanced algorithms, and concurrency features.Starting with an in-depth analysis of the std::vector, this book highlights its pivotal role in the STL, progressing toward building your proficiency in utilizing vectors, managing memory, and leveraging iterators. The book then advances to STL’s data structures, including sequence containers, associative containers, and unordered containers, simplifying the concepts of container adaptors and views to enhance your knowledge of modern STL programming. Shifting the focus to STL algorithms, you’ll get to grips with sorting, searching, and transformations and develop the skills to implement and modify algorithms with best practices. Advanced sections cover extending the STL with custom types and algorithms, as well as concurrency features, exception safety, and parallel algorithms.By the end of this book, you’ll have transformed into a proficient STL practitioner ready to tackle real-world challenges and build efficient and scalable C++ applications.What you will learnStreamline data handling using the std::vectorMaster advanced usage of STL iteratorsOptimize memory in STL containersImplement custom STL allocatorsApply sorting and searching with STL algorithmsCraft STL-compatible custom typesManage concurrency and ensure thread safety in STLHarness the power of parallel algorithms in STLWho this book is forThis book is for intermediate-level C++ developers looking to enhance their software development skills. Familiarity with basic C++ syntax and object-oriented programming (OOP) as well as some exposure to data structures and algorithms is assumed.Tailored to software engineers, computer science students, and hobbyist programmers, this book delves into C++ STL for practical application, performance enhancement, and efficient coding practices.
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Introduction to Data Structures and Algorithms
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
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Data Structures and Algorithms Using Visual Basic.NET
This is the first Visual Basic.NET book to provide a comprehensive discussion of the major data structures and algorithms. Here, instead of having to translate material on C++ or Java, the professional or student VB.NET programmer will find a tutorial on how to use data structures and algorithms and a reference for implementation using VB.NET for data structures and algorithms from the .NET Framework Class Library as well as those which must be developed by the programmer. In an object-oriented fashion, the author presents arrays and arraylists, linked lists, hash tables, dictionaries, trees, graphs, sorting and searching as well as more advanced algorithms, such as probabilistic algorithms and dynamic programming. His approach is very practical, for example using timing tests rather than Big O analysis to compare the performance of data structures and algorithms. This book can be used in both beginning and advanced computer programming courses that use the VB.NET language and, most importantly, by the professional VB programmer.
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Practical C++ Game Programming with Data Structures and Algorithms
Learn C++ game programming through real-world demos of AI systems, animation, and rendering to build scalable, high-performance games using patterns you can reuse across any game engineKey FeaturesBuild real-time 2D and 3D games using C++ with practical, executable examplesGain proficiency in game programming domains like AI pathfinding, camera systems, animation, and rendering effectsBoost runtime efficiency with practical techniques like object pooling, LOD patterns, and terrain partitioning to create smoother, more responsive gameplay systemsBook DescriptionCreating responsive, intelligent games takes more than just following engine tutorials. It requires solving real development challenges with practical, efficient code. This book bridges theory and practice with proven algorithms and techniques grounded in real-world production needs, emphasizing clean, portable C++ implementations.Starting with raylib and the custom Knight engine layer, you’ll be introduced to a simple object-oriented scene and game object system. From there, you'll build responsive gameplay systems using essential data structures and algorithms, progressing through 2D rendering, collision detection, effects, and camera control before advancing to 3D graphics environments built using shaders, lighting, quad-tree terrain, and dynamic camera setups.You’ll animate characters using skeletal rigs, interpolation, and inverse kinematics for fluid movement and then develop game AI using FSMs, behavior trees, A* pathfinding, and steering behaviors. The book also covers neural networks, exploring their underlying theories, training processes, and tools. Throughout, the code is written in legacy-compatible C++ to ensure broad support across platforms and compilers.By the end, you’ll have gained the skills to build game systems that not only work but also scale, perform, and adapt like professional-grade code.What you will learnUse C++ data structures and algorithms to build core gameplay featuresImplement 2D/3D rendering with shaders, particle effects, and terrain systemsDesign camera systems like third-person, top-down, and split-screen viewsOptimize performance using object pooling and LODAnimate characters using skeletal rigging, interpolation, and inverse kinematicsBuild game AI with FSMs, behavior trees, pathfinding, and steeringApply neural network concepts in a turret defense projectWho this book is forThis book is for junior game developers, hobbyists, and computer science students entering game development, as well as C++ programmers looking to strengthen their skills. While some familiarity with C++ is helpful, the examples are explained step by step to remain approachable. Whether you're starting out or reinforcing your skills before diving into game engines down the road, this book offers a clear and practical foundation to make you a more effective developer, regardless of which tools you choose later.
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Object-Orientation, Abstraction, and Data Structures Using Scala
Praise for the first edition:"The well-written, comprehensive book…[is] aiming to become a de facto reference for the language and its features and capabilities. The pace is appropriate for beginners; programming concepts are introduced progressively through a range of examples and then used as tools for building applications in various domains, including sophisticated data structures and algorithms…Highly recommended. Students of all levels, faculty, and professionals/practitioners. —D. Papamichail, University of Miami in CHOICE MagazineMark Lewis’ Introduction to the Art of Programming Using Scala was the first textbook to use Scala for introductory CS courses. Fully revised and expanded, the new edition of this popular text has been divided into two books. Object-Orientation, Abstraction, and Data Structures Using Scala, Second Edition is intended to be used as a textbook for a second or third semester course in Computer Science.The Scala programming language provides powerful constructs for expressing both object orientation and abstraction. This book provides students with these tools of object orientation to help them structure solutions to larger, more complex problems, and to expand on their knowledge of abstraction so that they can make their code more powerful and flexible. The book also illustrates key concepts through the creation of data structures, showing how data structures can be written, and the strengths and weaknesses of each one. Libraries that provide the functionality needed to do real programming are also explored in the text, including GUIs, multithreading, and networking. The book is filled with end-of-chapter projects and exercises, and the authors have also posted a number of different supplements on the book website. Video lectures for each chapter in the book are also available on YouTube. The videos show construction of code from the ground up and this type of "live coding" is invaluable for learning to program, as it allows students into the mind of a more experienced programmer, where they can see the thought processes associated with the development of the code. About the AuthorsMark Lewis is an Associate Professor at Trinity University. He teaches a number of different courses, spanning from first semester introductory courses to advanced seminars. His research interests included simulations and modeling, programming languages, and numerical modeling of rings around planets with nearby moons. Lisa Lacher is an Assistant Professor at the University of Houston, Clear Lake with over 25 years of professional software development experience. She teaches a number of different courses spanning from first semester introductory courses to graduate level courses. Her research interests include Computer Science Education, Agile Software Development, Human Computer Interaction and Usability Engineering, as well as Measurement and Empirical Software Engineering.
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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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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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Grokking Data Structures
Don’t be perplexed by data structures! This fun, friendly, and fully illustrated guide makes it easy to learn useful data structures you'll put to work every day. Grokking Data Structures makes it a breeze to learn the most useful day-to-day data structures. You'll follow a steady learning path from absolute basics to advanced concepts, all illustrated with fun examples, engaging industry stories, and hundreds of graphics and cartoons. In Grokking Data Structures you'll learn how to: Understand the most important and widely used data structuresIdentify use cases where data structures make the biggest differencePick the best data structure solution for a coding challengeUnderstand the tradeoffs of data structures and avoid catastrophesImplement basic data collections like arrays, linked lists, stacks, and priority queuesUse trees and binary search trees (BSTs) to organize dataUse graphs to model relationships and learn about complex dataEfficiently search by key using hash tables and hashing functionsReason about time and memory requirements of operations on data structures Grokking Data Structures carefully guides you from the most basic data structures like arrays or linked lists all the way to powerful structures like graphs. It’s perfect for beginners, and you won't need anything more than high school math to get started. Each data structure you encounter comes with its own complete Python implementation so you can start experimenting with what you learn right away. About the technology Data structures are vital for shaping and handling your data organization. They're also an important part of most IT job interviews! Whether you're new to data structures or just dusting off what you learned in school, this book will get you up to speed fast with no advanced math, abstract theory, or complicated proofs.
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Data Structures using Python
Data Structures using Python provides an introduction to design, analysis, and implementation of data structures using the powerful language Python. This book is designed for a first course on the subject. It is written for the undergraduate engineering students of Computer Science, Information Technology and allied disciplines.The book begins with an overview of the concept, need, nomenclature followed by discussion of Arrays, Stacks, Queues, Double Ended Queues, Linked List - all under a chapter on Linear Data Structures. This is followed by a chapter on Non-linear Data Structures where Heap, Hash Table, Trie, and Disjoint Sets are discussed. Trees, though a non-linear data structure, is discussed as a separate chapter to emphasize upon its importance. The last few chapters of the book discusses Graphs, Searching,and Sorting finally ending with an appendix on Python built-in class functions.
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Data Structures and Algorithms with JavaScript
As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms - including linked lists, stacks, queues, and graphs - within the constraints of the JavaScript environment. Determine which data structures and algorithms are most appropriate for the problems you're trying to solve, and understand the tradeoffs when using them in a JavaScript program. An overview of the JavaScript features used throughout the book is also included.This book covers: Arrays and lists: the most common data structures Stacks and queues: more complex list-like data structures Linked lists: how they overcome the shortcomings of arrays Dictionaries: storing data as key-value pairs Hashing: good for quick insertion and retrieval Sets: useful for storing unique elements that appear only once Binary Trees: storing data in a hierarchical manner Graphs and graph algorithms: ideal for modeling networks Algorithms: including those that help you sort or search data Advanced algorithms: dynamic programming and greedy algorithms
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Data Structures for Engineers and Scientists Using Python
The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using the queue model and topological sorting.This book:Discusses the implementation of various data structures such as an array, stack, queue, tree and graph along with sorting and searching algorithms. Includes programming tips to highlight important concepts and help readers avoid common programming errors. Presents each concept of data structure with a different approach and implements the same using Python programming. Offers rich chapter-end pedagogy including objective-type questions (with answers), review questions and programming exercises to facilitate review. Covers fundamentals of Python up to object-oriented concepts including regular expression. It is primarily written for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering and information technology.
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