Search results for "Data Structures using C"
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R 306.00
R 814.00
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Head First Algorithms and Data Structures
What will you learn from this book?Successful software engineers all have this in common: They're fluent in the language of algorithms and data structures. Head First Algorithms and Data Structures is your gateway to becoming a part of this dynamic world. Guided by the expert insights of Eric Freeman and Elisabeth Robson, you'll unravel the complexities of algorithms and data structures through games, puzzles, and other entertaining challenges that will have you coding efficiently, scaling effectively, and acing your technical interviews in no time.What's so special about this book?If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. Whether you're taking your first steps in programming or seeking to hone your skills, you'll solidify your algorithmic thinking through a multisensory experience that engages your mind—not a text-heavy approach that puts you to sleep.
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R 519.00
Genetic Programming and Data Structures
Computers that `program themselves' has long been an aim of computer scientists. Recently genetic programming (GP) has started to show its promise by automatically evolving programs. Indeed in a small number of problems GP has evolved programs whose performance is similar to or even slightly better than that of programs written by people. The main thrust of GP has been to automatically create functions. While these can be of great use they contain no memory and relatively little work has addressed automatic creation of program code including stored data. This issue is the main focus of Genetic Programming, and Data Structures: Genetic Programming + Data Structures = Automatic Programming!. This book is motivated by the observation from software engineering that data abstraction (e.g., via abstract data types) is essential in programs created by human programmers. This book shows that abstract data types can be similarly beneficial to the automatic production of programs using GP. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! shows how abstract data types (stacks, queues and lists) can be evolved using genetic programming, demonstrates how GP can evolve general programs which solve the nested brackets problem, recognises a Dyck context free language, and implements a simple four function calculator. In these cases, an appropriate data structure is beneficial compared to simple indexed memory. This book also includes a survey of GP, with a critical review of experiments with evolving memory, and reports investigations of real world electrical network maintenance scheduling problems that demonstrate that Genetic Algorithms can find low cost viable solutions to such problems. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! should be of direct interest to computer scientists doing research on genetic programming, genetic algorithms, data structures, and artificial intelligence. In addition, this book will be of interest to practitioners working in all of these areas and to those interested in automatic programming.
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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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Essential Data Structures and Algorithms in Java
Master essential data structures and algorithms in Java with clear examples, visual walkthroughs, and real-world coding exercises designed to build your problem-solving skills fastKey FeaturesBuild solid foundations with a complete overview of core DSA conceptsImplement advanced data structures for AI agents and complex systemsMaster Java Collections and complexity analysis for scalable applicationsVisualize and debug algorithms with detailed annotated walkthroughsBook DescriptionDeveloping efficient, reliable software starts with mastering data structures and algorithms. This practical guide helps you bridge theory and practice using Java, focusing on real-world challenges and pragmatic solutions. You will explore foundational data structures such as arrays, lists, stacks, queues, trees, and graphs, and learn how to implement them natively and leverage the Java Collections Framework to build scalable applications. With each concept, you will work through step-by-step exercises that illustrate how algorithms are applied to tasks such as searching, sorting, and traversing data.Rather than being theory-heavy or overly abstract, this book takes a problem-first approach, balancing conceptual explanations with immediate hands-on application. Visual walkthroughs, annotated code, and progressive exercises guide you through each concept, helping you internalize how different structures and algorithms impact performance. Each chapter ends with review problems and thought exercises designed to reinforce key ideas and build your confidence through practice.Guided by a veteran software engineer with over 20 years of industry experience, you will gain the skills to implement advanced data structures for modern software systems and write faster, cleaner, and more effective Java code in real development environments.What you will learnUnderstand and implement core data structures in JavaAnalyze time and space complexity with Big O notationSolve coding problems with arrays, linked lists, and hash mapsUse stacks and queues to manage linear data workflowsApply tree and graph algorithms to hierarchical and networked dataMaster dynamic programming approachesDesign concurrent applications using Java's built-in toolsEvaluate algorithmic trade-offs for real-world applications including AIWho this book is forPerfect for aspiring Java developers, CS students, and software engineers with a foundation in JDK 11+ and OOP looking for a practical DSA refresher. This book skips basic syntax tutorials to front-load core principles, allowing you to turn theory into high-performance logic. Master complex algorithms and apply proven problem-solving patterns to write faster, cleaner, and AI-native Java code.
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VLSI Architecture for Concurrent Data Structures
Concurrent data structures simplify the development of concurrent programs by encapsulating commonly used mechanisms for synchronization and commu nication into data structures. This thesis develops a notation for describing concurrent data structures, presents examples of concurrent data structures, and describes an architecture to support concurrent data structures. Concurrent Smalltalk (CST), a derivative of Smalltalk-80 with extensions for concurrency, is developed to describe concurrent data structures. CST allows the programmer to specify objects that are distributed over the nodes of a concurrent computer. These distributed objects have many constituent objects and thus can process many messages simultaneously. They are the foundation upon which concurrent data structures are built. The balanced cube is a concurrent data structure for ordered sets. The set is distributed by a balanced recursive partition that maps to the subcubes of a binary 7lrcube using a Gray code. A search algorithm, VW search, based on the distance properties of the Gray code, searches a balanced cube in O(log N) time. Because it does not have the root bottleneck that limits all tree-based data structures to 0(1) concurrency, the balanced cube achieves 0C.:N) con currency. Considering graphs as concurrent data structures, graph algorithms are pre sented for the shortest path problem, the max-flow problem, and graph parti tioning. These algorithms introduce new synchronization techniques to achieve better performance than existing algorithms.
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Construction of Fundamental Data Structures for Strings
This books reviews recent theoretical and practical advances on suffix sorting and introduces algorithmic solutions to problems of wide interest for the construction of fundamental data structures that operate efficiently on strings namely, constructing the suffix array, the longest common prefix (LCP) array, the document array and the Lyndon array. These data structures are the cornerstone of many algorithmic solutions in Bioiformatics, Information Retrieval and Data Compression. This book introduces the relevant problem areas, their importance, the notation and related algorithms and then presents the algorithmic solutions for indexing data structure constructions.This book is intended for graduate students, researchers and practitioners from Computer Science and Bioinformatics with a strong interest in algorithmic aspects.
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Structured Programming Approach to Data
Much of current programming practice is basically empirical and ad hoc in approach. Each problem is tackled without relation to those that have gone before; experiences are made and stored as a series of fragments. Now, under the pressure of events, this unsatisfactory state of affairs is coming to an end. Programming is becoming a technology, a theory known as structured programming is developing. The purpose of a theory is to categorise and explain existing practice, thus enabling it to be improved through the development of new and sharper techniques. The resulting experiences have then to be fed back into the theory so that the process of enrichment may continue. This dialectical relationship between theory and practice is essential to a healthy programming technology. The lack of such a relationship in the 1950s and 60s and the accompanying software crisis certainly confirm the converse of this proposition. My aim in writing this book has been to explain the current state of the theory of structured programming, so that it may be used to improve the reader's practice. The book deals with two facets of programming - how to design a program in terms of abstract data structures and how to represent the data structures on real and bounded computers. The separation between program design and data structure representation leads to more reliable and flexible programs.
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Introduction to Computational Modeling Using C and Open-Source Tools
Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing the data. All source files, shell scripts, and additional notes are located at ksuweb.kennesaw.edu/~jgarrido/compmodels.The book first presents an overview of problem solving and the introductory concepts, principles, and development of computational models before covering the programming principles of the C programming language. The author then applies programming principles and basic numerical techniques, such as polynomial evaluation, regression, and other numerical methods, to implement computational models. He also discusses more advanced concepts needed for modeling dynamical systems and explains how to generate numerical solutions. The book concludes with the modeling of linear optimization problems.Emphasizing analytical skill development and problem solving, this book helps you understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides you with the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.
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Modular Calculus for the Average Cost of Data Structuring
This book introduces the first programming language for which average-case time analysis of its programs is guaranteed to be modular. The main time measure currently used for real-time languages (worst-case time) is well-known not to be modular in general, which makes average-case analysis notoriously difficult. Schellekens includes sample programs as well as derivations of the average-case time of these programs to illustrate this radically different approach.
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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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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
The papers in this volume were presented at the 9th Workshop on Algorithms and Data Structures (WADS 2005). The workshop took place during August 15 - 17, 2005, at the University of Waterloo, Waterloo, Canada. The workshop alternateswith the ScandinavianWorkshopon Algorithm Theory(SWAT), c- tinuing the traditionof SWAT and WADS startingwith SWAT 1988and WADS 1989. From 90 submissions, the Program Committee selected 37 papers for p- sentation at the workshop. In addition, invited lectures were given by the f- lowing distinguished researchers: Allan Borodin and Max J. Egenhofer. OnbehalfoftheProgramCommittee,wewouldliketoexpressoursincere- preciation to the many persons whose e?ort contributed to making WADS 2005 a success. These include the invited speakers,members of the ste- ing and ProgramCommittees, the authors who submitted papers, and the many referees who assisted the ProgramCommittee. We are indebted to Robert Kane forinstallingandmodifyingthesubmissionsoftware,maintainingthesubmission server and interacting with authors as well as for helping with the preparation of the program. August 2005 Frank Dehne, Alejandro Lop ' ez-Ortiz, and Jorg-R .. u ..diger Sack WADS Organization Organizing Institutions Steering Committee Frank Dehne Carleton University, Canada Ian Munro University of Waterloo, Canada J.. org-Rudig .. er Sack Carleton University, Canada Roberto Tamassia Brown University, Canada Program Co-chairs Frank Dehne Carleton University, Canada Alejandro Lop ' ez-Ortiz University of Waterloo, Canada J.. org-Rudig .. er Sack Carleton University, Canada Conference Chair Alejandro Lop ' ez-Ortiz University of Waterloo, Canada Program Committee Pankaj Agarwal Duke University, USA Michael Atkinson University of Otago, New Zealand Gill Barequet Technion, Israel Mark de Berg Tech.
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Data Structure and Software Engineering
This title includes a number of Open Access chapters.Data structure and software engineering is an integral part of computer science. This volume presents new approaches and methods to knowledge sharing, brain mapping, data integration, and data storage. The author describes how to manage an organization’s business process and domain data and presents new software and hardware testing methods. The book introduces a game development framework used as a learning aid in a software engineering at the university level. It also features a review of social software engineering metrics and methods for processing business information. It explains how to use Pegasys to create and manage sequence analysis workflows.
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