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Algorithms On Trees And Graphs

Author: Gabriel Valiente
Publisher: Springer Science & Business Media
ISBN: 366204921X
Size: 26.76 MB
Format: PDF, ePub
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Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.

Algorithms On Trees And Graphs

Author: Gabriel Valiente
Publisher: Springer Science & Business Media
ISBN: 9783540435501
Size: 41.41 MB
Format: PDF, ePub, Mobi
View: 5837
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Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.

Graph Theory For Programmers

Author: Victor N. Kasyanov
Publisher: Springer Science & Business Media
ISBN: 9780792364283
Size: 46.74 MB
Format: PDF, Kindle
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This introductory book treats algorithmic graph theory specifically for programmers. It explores some key ideas and basic algorithms in this large and rapidly growing field, and contains high-level and language-independent descriptions of methods and algorithms on trees, the most important type of graphs in programming and informatics. Readers are assumed to be familiar with the basics of graph theory, and programming. Audience: This volume will be of interest to researchers and specialists in programming, software engineering, data structure and information retrieval, and to mathematicians whose work involves algorithms, combinatorics, graph theory, operations research, and discrete optimization. The book can also be recommended as a text for graduate courses in computer science, electronics, telecommunications, and control engineering.

Graph Theory And Computing

Author: Ronald C. Read
Publisher: Academic Press
ISBN: 1483263126
Size: 43.87 MB
Format: PDF, Mobi
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Graph Theory and Computing focuses on the processes, methodologies, problems, and approaches involved in graph theory and computer science. The book first elaborates on alternating chain methods, average height of planted plane trees, and numbering of a graph. Discussions focus on numbered graphs and difference sets, Euclidean models and complete graphs, classes and conditions for graceful graphs, and maximum matching problem. The manuscript then elaborates on the evolution of the path number of a graph, production of graphs by computer, and graph-theoretic programming language. Topics include FORTRAN characteristics of GTPL, design considerations, representation and identification of graphs in a computer, production of simple graphs and star topologies, and production of stars having a given topology. The manuscript examines the entropy of transformed finite-state automata and associated languages; counting hexagonal and triangular polyominoes; and symmetry of cubical and general polyominoes. Graph coloring algorithms, algebraic isomorphism invariants for graphs of automata, and coding of various kinds of unlabeled trees are also discussed. The publication is a valuable source of information for researchers interested in graph theory and computing.

Graph Algorithms

Author: Shimon Even
Publisher: Cambridge University Press
ISBN: 1139504150
Size: 31.49 MB
Format: PDF, ePub, Docs
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Shimon Even's Graph Algorithms, published in 1979, was a seminal introductory book on algorithms read by everyone engaged in the field. This thoroughly revised second edition, with a foreword by Richard M. Karp and notes by Andrew V. Goldberg, continues the exceptional presentation from the first edition and explains algorithms in a formal but simple language with a direct and intuitive presentation. The book begins by covering basic material, including graphs and shortest paths, trees, depth-first-search and breadth-first search. The main part of the book is devoted to network flows and applications of network flows, and it ends with chapters on planar graphs and testing graph planarity.

Swift Data Structure And Algorithms

Author: Erik Azar
Publisher: Packt Publishing Ltd
ISBN: 1785884654
Size: 79.66 MB
Format: PDF, ePub, Docs
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Master the most common algorithms and data structures, and learn how to implement them efficiently using the most up-to-date features of Swift 3 About This Book Develop a deep understanding of the collections in the Swift Standard Library with this step-by-step guide Develop native Swift data structures and algorithms for use in mobile, desktop, and server-based applications Learn about performance efficiency between different data structures and algorithms Who This Book Is For This book is for developers who want to learn how to implement and use common data structures and algorithms natively in Swift. Whether you are a self-taught developer without a formal technical background or you have a degree in Computer Science, this book will provide with the knowledge you need to develop advanced data structures and algorithms in Swift using the latest language features. What You Will Learn Get to know about the basic data structures and how to use the Swift REPL Use the Swift Standard Library collections bridging to Objective-C collections, and find out about protocol-oriented programming Find out about Swift generators and sequences, and see how to use them to implement advanced data structures such as Stack, StackList, Queue, and LinkedList Implement sorting algorithms such as Insertion Sort, Merge Sort, and Quick Sort and understand the performance trade-offs between them See how to implement various binary trees, B-Tree, and Splay Trees Perform advanced searching methods using Red-Black trees, AVL trees, and Trie trees, and take a look at several substring search algorithms Get to know about the data structures used in graphs and how to implement graphs such as depth-first search, breadth-first search, directed graphs, spanning tree, and shortest path Explore algorithm efficiency and see how to measure it In Detail Apple's Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple's legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That's what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You'll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You'll also see how to choose the perfect algorithm for your problem. Style and approach This easy-to-follow yet comprehensive guide can either be read from beginning to end, or depending on your current knowledge level, you can jump to the specific chapter that interests you. Each chapter topic starts with an introduction to the topic and algorithm before moving on to the hands-on implementation and analysis.

C Data Structures And Algorithms

Author: Marcin Jamro
Publisher: Packt Publishing Ltd
ISBN: 1788834682
Size: 29.48 MB
Format: PDF, Docs
View: 1938
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A complete guide on using data structures and algorithms to write sophisticated C# code Key Features Master array, set and map with trees and graphs, among other fundamental data structures Delve into effective design and implementation techniques to meet your software requirements Explore illustrations to present data structures and algorithms, as well as their analysis in a clear, visual manner. Book Description Data structures allow organizing data efficiently. They are critical to various problems and their suitable implementation can provide a complete solution that acts like reusable code. In this book, you will learn how to use various data structures while developing in the C# language as well as how to implement some of the most common algorithms used with such data structures. At the beginning, you will get to know arrays, lists, dictionaries, and sets together with real-world examples of your application. Then, you will learn how to create and use stacks and queues. In the following part of the book, the more complex data structures will be introduced, namely trees and graphs, together with some algorithms for searching the shortest path in a graph. We will also discuss how to organize the code in a manageable, consistent, and extendable way. By the end of the book,you will learn how to build components that are easy to understand, debug, and use in different applications. What you will learn How to use arrays and lists to get better results in complex scenarios Implement algorithms like the Tower of Hanoi on stacks of C# objects Build enhanced applications by using hashtables, dictionaries and sets Make a positive impact on efficiency of applications with tree traversal Effectively find the shortest path in the graph Who this book is for This book is for developers who would like to learn the Data Structures and Algorithms in C#. Basic C# programming knowledge would be an added advantage.

R Data Structures And Algorithms

Author: Dr. PKS Prakash
Publisher: Packt Publishing Ltd
ISBN: 1786464160
Size: 19.20 MB
Format: PDF, Mobi
View: 6651
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Increase speed and performance of your applications with efficient data structures and algorithms About This Book See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and sorting algorithms Understand important concepts such as big-o notation, dynamic programming, and functional data structured Who This Book Is For This book is for R developers who want to use data structures efficiently. Basic knowledge of R is expected. What You Will Learn Understand the rationality behind data structures and algorithms Understand computation evaluation of a program featuring asymptotic and empirical algorithm analysis Get to know the fundamentals of arrays and linked-based data structures Analyze types of sorting algorithms Search algorithms along with hashing Understand linear and tree-based indexing Be able to implement a graph including topological sort, shortest path problem, and Prim's algorithm Understand dynamic programming (Knapsack) and randomized algorithms In Detail In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. Style and approach This easy-to-read book with its fast-paced nature will improve the productivity of an R programmer and improve the performance of R applications. It is packed with real-world examples.

Mastering Algorithms With C

Author: Kyle Loudon
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596551957
Size: 69.35 MB
Format: PDF, Docs
View: 6991
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There are many books on data structures and algorithms, including some with useful libraries of C functions. Mastering Algorithms with C offers you a unique combination of theoretical background and working code. With robust solutions for everyday programming tasks, this book avoids the abstract style of most classic data structures and algorithms texts, but still provides all of the information you need to understand the purpose and use of common programming techniques. Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included. Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth. Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters. Contents include: Pointers Recursion Analysis of algorithms Data structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs) Sorting and searching Numerical methods Data compression Data encryption Graph algorithms Geometric algorithms