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Useful for readers who want to visualize graphs as representing structural knowledge in a variety of fields.
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.
This book constitutes the refereed proceedings of the 28th International Symposium on Graph Drawing and Network Visualization, GD 2020, which was held during September 16-18, 2020. The conference was planned to take place in Vancouver, Canada, but changed to an online format due to the COVID-19 pandemic. The 29 full and 9 short papers presented in this volume were carefully reviewed and selected from 82 submissions. They were organized in topical sections named: gradient descent and queue layouts; drawing tree-like graphs, visualization, and special drawings of elementary graphs; restricted drawings of special graph classes; orthogonality; topological constraints; crossings, k-planar graphs; planarity; graphs drawing contest.
This book presents the state of the art in software visualization and thus attempts to establish it as a field on its own. Based on a seminar held at Dagstuhl Castle in May 2001, the book offers topical sections on: - algorithm animation - software visualization and software engineering - software visualization and education - graphs in software visualization - and perspectives of software visualization. Each section starts with an introduction surveying previous and current work and providing extensive bibliographies.
This book constitutes the refereed proceedings of the 27th International Symposium on Graph Drawing and Network Visualization, GD 2019, held in Prague, Czech Republic, in September 2019. The 42 papers and 12 posters presented in this volume were carefully reviewed and selected from 113 submissions. They were organized into the following topical sections: Cartograms and Intersection Graphs, Geometric Graph Theory, Clustering, Quality Metrics, Arrangements, A Low Number of Crossings, Best Paper in Track 1, Morphing and Planarity, Parameterized Complexity, Collinearities, Topological Graph Theory, Best Paper in Track 2, Level Planarity, Graph Drawing Contest Report, and Poster Abstracts.
Automatic layout is an important tool for the efficient use of graphical models in a model-driven engineering (MDE) context. Since the 1980s, research on graph layout methods has led to a multitude of different approaches, and several free software libraries for graph layout are available. However, today's practically relevant MDE tools hardly reflect this diversity. This thesis aims to support the use of automatic graph layout in such tools. A special focus is on the requirements of data flow models, where constraints on the positioning of ports and the routing of hyperedges pose additional challenges. These constraints are approached with extensions of the layer-based graph layout method. Furthermore, we discuss an infrastructure for managing collections of layout algorithms, allowing to flexibly specify layout configurations. These concepts are implemented in an open-source project based on Eclipse, an extensible platform that is well-known as a Java IDE and also hosts a large number of MDE tools. The presented contributions allow to integrate high-quality automatic layout into these tools with low effort.
The Handbook of Graph Theory is the most comprehensive single-source guide to graph theory ever published. Best-selling authors Jonathan Gross and Jay Yellen assembled an outstanding team of experts to contribute overviews of more than 50 of the most significant topics in graph theory-including those related to algorithmic and optimization approach
This volume gives an overview on new theoretical approaches on computer-aided methods for strategic and operational planning in public transport. The papers of this volume cover the most important steps of the complete process of planning and operational control in public transport and public mass transit. Readers of this book obtain detailed information on current developments in vehicle and crew scheduling and in solving such problems in practice. Interesting results in scheduling theory are shown, using procedures for solving combinatorial problems with more complex structures. Furthermore, experiences in the application of specific software tools are presented. TOC:Vehicle and Crew Scheduling - Methodical Advances.- Vehicle and Crew Scheduling - Practical Issues.- Advanced Transit Service and Vehicle Routing.- Monitoring and Control.- Strategic Decision Problems.- Appendices.
The first volume of this popular handbook mirrors the modern taxonomy of computer science and software engineering as described by the Association for Computing Machinery (ACM) and the IEEE Computer Society (IEEE-CS). Written by established leading experts and influential young researchers, it examines the elements involved in designing and implementing software, new areas in which computers are being used, and ways to solve computing problems. The book also explores our current understanding of software engineering and its effect on the practice of software development and the education of software professionals.