Search results for "Data Structures and Algorithms in Java"
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Beginning Algorithms
Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursionElementary data structures such as lists, stacks, and queuesBasic and advanced sorting algorithms including insertion sort, quicksort, and shell sortAdvanced data structures such as binary trees, ternary trees, and heapsAlgorithms for string searching, string matching, hashing, and computational geometryHow to use test-driven development techniques to ensure your code works as intendedHow to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.
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Quick Data Structures
If you want to upgrade your programming skills, the most important thing you need is a solid understanding of fundamental data structures. The proper choice of data structures distinguishes excellent programmers from merely competent ones.As an experienced programmer, you use data structures—at least arrays—all the time. However, you may not be familiar with hash tables, trees and binary trees, priority queues, directed and undirected graphs, and other data structures at your disposal.A good choice of data structures will simplify your job, not complicate it. Your code will be not only faster but also easier to understand and debug. There is no downside to using the right data structures for the job.This book Provides an understanding of the fundamental building blocks of data structures Describes the construction and use of all common data structures Explains the simple math required for selecting efficient data structures Equips you with everything you need to choose data structures or devise appropriate new ones
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Java Library of Graph Algorithms and Optimization
Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph algorithms and other mathematical programming problems. Collecting some of the most popular graph algorithms and optimization procedures, A Java Library of Graph Algorithms and Optimization provides the source code for a library of Java programs that can be used to solve problems in graph theory and combinatorial optimization. Self-contained and largely independent, each topic starts with a problem description and an outline of the solution procedure, followed by its parameter list specification, source code, and a test example that illustrates the usage of the code.The book begins with a chapter on random graph generation that examines bipartite, regular, connected, Hamilton, and isomorphic graphs as well as spanning, labeled, and unlabeled rooted trees. It then discusses connectivity procedures, followed by a paths and cycles chapter that contains the Chinese postman and traveling salesman problems, Euler and Hamilton cycles, and shortest paths. The author proceeds to describe two test procedures involving planarity and graph isomorphism. Subsequent chapters deal with graph coloring, graph matching, network flow, and packing and covering, including the assignment, bottleneck assignment, quadratic assignment, multiple knapsack, set covering, and set partitioning problems. The final chapters explore linear, integer, and quadratic programming. The appendices provide references that offer further details of the algorithms and include the definitions of many graph theory terms used in the book.
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Quick Data Structures
If you want to upgrade your programming skills, the most important thing you need is a solid understanding of fundamental data structures. The proper choice of data structures distinguishes excellent programmers from merely competent ones.As an experienced programmer, you use data structures—at least arrays—all the time. However, you may not be familiar with hash tables, trees and binary trees, priority queues, directed and undirected graphs, and other data structures at your disposal.A good choice of data structures will simplify your job, not complicate it. Your code will be not only faster but also easier to understand and debug. There is no downside to using the right data structures for the job.This book Provides an understanding of the fundamental building blocks of data structures Describes the construction and use of all common data structures Explains the simple math required for selecting efficient data structures Equips you with everything you need to choose data structures or devise appropriate new ones
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Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
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Genetic Algorithms + Data Structures = Evolution Programs
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science.The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.
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Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
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Algorithms for Functional Programming
This book presents a variety of widely used algorithms, expressing them in a pure functional programming language to make their structure and operation clearer to readers. In the opening chapter the author introduces the specific notations that constitute the variant of Scheme that he uses. The second chapter introduces many of the simpler and more general patterns available in functional programming. The chapters that follow introduce and explain data structures, sorting, combinatorial constructions, graphs, and sublist search.Throughout the book the author presents the algorithms in a purely functional version of the Scheme programming language, which he makes available on his website. The book is supported with exercises, and it is suitable for undergraduate and graduate courses on programming techniques.
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Correspondence Analysis and Data Coding with Java and R
Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever.Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzécri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields.This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.
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Algorithms and Data Structures in VLSI Design
One of the main problems in chip design is the enormous number of possible combinations of individual chip elements within a system, and the problem of their compatibility. The recent application of data structures, efficient algorithms, and ordered binary decision diagrams (OBDDs) has proven vital in designing the computer chips of tomorrow. This book provides an introduction to the foundations of this interdisciplinary research area, emphasizing its applications in computer aided circuit design.
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Foundations of Multidimensional and Metric Data Structures
Foundations of Multidimensional and Metric Data Structures provides a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions. The book is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.
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New Data Structures and Algorithms for Logic Synthesis and Verification
This book introduces new logic primitives for electronic design automation tools. The author approaches fundamental EDA problems from a different, unconventional perspective, in order to demonstrate the key role of rethinking EDA solutions in overcoming technological limitations of present and future technologies. The author discusses techniques that improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. Readers will be enabled to accelerate formal methods by studying core properties of logic circuits and developing new frameworks for logic reasoning engines.
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Algorithms and Order
This volume contains the texts of the principal survey papers presented at ALGORITHMS -and ORDER, held· at Ottawa, Canada from June 1 to June 12, 1987. The conference was supported by grants from the N.A.T.O. Advanced Study Institute programme, the University of Ottawa, and the Natural Sciences and Engineering Research Council of Canada. We are grateful for this considerable support. Over fifty years ago, the Symposium on Lattice Theory, in Charlottesville, U.S.A., proclaimed the vitality of ordered sets. Only twenty years later the Symposium on Partially Ordered Sets and Lattice Theory, held at Monterey, U.S.A., had solved many of the problems that had been originally posed. In 1981, the Symposium on Ordered Sets held at Banff, Canada, continued this tradition. It was marked by a landmark volume containing twenty-three articles on almost all current topics in the theory of ordered sets and its applications. Three years after, Graphs and Orders, also held at Banff, Canada, aimed to document the role of graphs in the theory of ordered sets and its applications. Because of its special place in the landscape of the mathematical sciences order is especially sensitive to new trends and developments. Today, the most important current in the theory and application of order springs from theoretical computer seience. Two themes of computer science lead the way. The first is data structure. Order is common to data structures.
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Algorithms and Discrete Applied Mathematics
This book constitutes the proceedings of the 4th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2018, held in Guwahati, India, in February 2018. The 23 papers presented in this volume were carefully reviewed and selected from 68 submissions. They focus on topics related to efficient algorithms and data structures, their analysis (both theoretical and experimental). The mathematical problems arising thereof, and new applications of discrete mathematics, advances in existing applications and development of new tools for discrete mathematics.
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Advanced Data Structures
Advanced data structures is a core course in Computer Science which most graduate program in Computer Science, Computer Science and Engineering, and other allied engineering disciplines, offer during the first year or first semester of the curriculum. The objective of this course is to enable students to have the much-needed foundation for advanced technical skill, leading to better problem-solving in their respective disciplines. Although the course is running in almost all the technical universities for decades, major changes in the syllabus have been observed due to the recent paradigm shift of computation which is more focused on huge data and internet-based technologies. Majority of the institute has been redefined their course content of advanced data structure to fit the current need and course material heavily relies on research papers because of nonavailability of the redefined text book advanced data structure. To the best of our knowledge well-known textbook on advanced data structure provides only partial coverage of the syllabus. The book offers comprehensive coverage of the most essential topics, including: Part I details advancements on basic data structures, viz., cuckoo hashing, skip list, tango tree and Fibonacci heaps and index files. Part II details data structures of different evolving data domains like special data structures, temporal data structures, external memory data structures, distributed and streaming data structures. Part III elucidates the applications of these data structures on different areas of computer science viz, network, www, DBMS, cryptography, graphics to name a few. The concepts and techniques behind each data structure and their applications have been explained. Every chapter includes a variety of Illustrative Problems pertaining to the data structure(s) detailed, a summary of the technical content of the chapter and a list of Review Questions, to reinforce the comprehension of the concepts. The book could be used both as an introductory or an advanced-level textbook for the advanced undergraduate, graduate and research programmes which offer advanced data structures as a core or an elective course. While the book is primarily meant to serve as a course material for use in the classroom, it could be used as a starting point for the beginner researcher of a specific domain.
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Algorithms and Computation
This book constitutes the refereed proceedings of the 25th International Symposium on Algorithms and Computation, ISAAC 2014, held in Jeonju, Korea, in December 2014. The 60 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 171 submissions for inclusion in the book. The focus of the volume in on the following topics: computational geometry, combinatorial optimization, graph algorithms: enumeration, matching and assignment, data structures and algorithms, fixed-parameter tractable algorithms, scheduling algorithms, computational complexity, computational complexity, approximation algorithms, graph theory and algorithms, online and approximation algorithms, and network and scheduling algorithms.
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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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Algorithms and Data Structures - Applications to Graphics and Geometry
This is a college-level introductory textbook of algorithms and data structures with application to graphics and geometry. This textbook, released under a Creative Commons Share Alike (CC BY SA) license, is presented in its original format with the academic content unchanged. It was authored by Jurg Nievergelt (ETH Zurich) and Klaus Hinrichs (Institut fur Informatik) and provided by the University of Georgia's Global Textbook Project. Textbookequity.org/algorithms-and-data-structures/ Photo Credit: Renato Keshet (GFDL) commons.wikimedia.org Contents Part I: Programming environments for motion, graphics, and geometry Part II: Programming concepts: beyond notation Part IV: Complexity of problems and algorithms Part V: Data structures Textbook Equity Edition http://textbookequity.org/algorithms-and-data-structures
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Algorithms
Algorithms play a central role both in the theory and in the practice of computing. The goal of the authors was to write a textbook that would not trivialize the subject but would still be readable by most students on their own. The book contains over 120 exercises. Some of them are drills; others make important points about the material covered in the text or introduce new algorithms not covered there. The book also provides programming projects. From the Table of Contents: Chapter 1: Basic knowledge of Mathematics, Relations, Recurrence relation and Solution techniques, Function and Growth of functions. Chapter 2: Different Sorting Techniques and their analysis. Chapter 3: Greedy approach, Dynamic Programming, Branch and Bound techniques, Backtracking and Problems, Amortized analysis, and Order Statics. Chapter 4: Graph algorithms, BFS, DFS, Spanning Tree, Flow Maximization Algorithms. Shortest Path Algorithms. Chapter 5: Binary search tree, Red black Tree, Binomial heap, B-Tree and Fibonacci Heap. Chapter 6: Approximation Algorithms, Sorting Networks, Matrix operations, Fast Fourier Transformation, Number theoretic Algorithm, Computational geometry Randomized Algorithms, String matching, NP-Hard, NP-Completeness, Cooks theorem.
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Numeric Computation and Statistical Data Analysis on the Java Platform
Numericalcomputation, knowledge discovery and statistical data analysis integrated withpowerful 2D and 3D graphics for visualization are the key topics of this book. ThePython code examples powered by the Java platform can easily be transformed toother programming languages, such as Java, Groovy, Ruby and BeanShell. Thisbook equips the reader with acomputational platform which, unlike other statistical programs, is not limitedby a single programming language.The authorfocuses on practical programming aspects and covers a broad range of topics,from basic introduction to the Python language on the Java platform (Jython),to descriptive statistics, symbolic calculations, neural networks, non-linearregression analysis and many other data-mining topics. He discusses how to findregularities in real-world data, how to classify data, and how to process datafor knowledge discoveries. The code snippets are so short that they easily fit intosingle pages.Numeric Computation and Statistical DataAnalysis on the Java Platform is a great choice for those who want to learn how statisticaldata analysis can be done using popular programming languages, who want tointegrate data analysis algorithms in full-scale applications, and deploy suchcalculations on the web pages or computational servers regardlessof their operating system. It is an excellent reference for scientific computations to solvereal-world problems using a comprehensive stack of open-source Javalibraries included in the DataMelt (DMelt) project and will beappreciated by many data-analysis scientists, engineers and students.
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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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