Bøger i Texts in Computer Science serien

An Integrated Approach to Software Engineering introduces software engineering to advanced-level undergraduate and graduate students of computer science. It emphasizes a case-study approach whereby a project is developed through the course of the book, illustrating the different activities of software development. The sequence of chapters is essentially the same as the sequence of activities performed during a typical software project. All activities, including quality assurance and control activities, are described in each chapter as integral activities for that phase of development. Similarly, the author carefully introduces appropriate metrics for controlling and assessing the software process.  Chapters in this revised edition, updated for today's standards, include these new features:Software Process: a discussion on the timeboxing model for iterative development and on inspection process Requirements Analysis and Specification: a description of Use Cases Software Architecture: an additional chapter for this edition Project Planning: some practical techniques for estimation, scheduling, tracking, and risk management Object Oriented Design: a discussion on UML and on concepts such as cohesion, coupling and open-closed principle Coding: sections on refactoring, test driven development, pair programming, common coding defects, coding standards, and some useful coding practices Testing: a presentation on pair-wise testing as an approach for functional testing, defect tracking, and defect analysis and prevention The text, bolstered by numerous examples and chapter summaries, imparts to the reader the knowledge, skills, practices and techniques needed to successfully execute a software project.

Differing from other books on the subject, this one uses the framework of constraint databases to provide a natural and powerful generalization of relational databases. An important theme running through the text is showing how relational databases can smoothly develop into constraint databases, without sacrificing any of the benefits of relational databases whilst gaining new advantages. Peter Revesz begins by discussing data models and how queries may be addressed to them. From here, he develops the theory of relational and constraint databases, including Datalog and the relational calculus, concluding with three sample constraint database systems -- DISCO, DINGO, and RATHER. Advanced undergraduates and graduates in computer science will find this a clear introduction to the subject, while professionals and researchers will appreciate this novel perspective on their subject.

By virtue of the close relationship between logic and relational databases, it turns out that complexity has important applications to databases such as analyzing the parallel time needed to compute a query, and the analysis of nondeterministic classes. This book is a relatively self-contained introduction to the subject, which includes the necessary background material, as well as numerous examples and exercises.

Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence.

This textbook aims to help the reader develop an in-depth understanding of logical reasoning and gain knowledge of the theory of computation. Content-wise, this book focuses on the syntax, semantics and proof theory of various logics; This book is written for a high-level undergraduate course or a Master's course.

This textbook is about systematic problem solving and systematic reasoning using type-driven design. Divide and conquer is the process by which a large problem is broken into two or more smaller problems that are easier to solve and then the solutions for the smaller pieces are combined to create an answer to the problem.

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.

This textbook treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, complexity theory, bounds and constructive algorithms.

This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced third edition has been fully revised and expanded with new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms. Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.

explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability;

Here is a hands-on treatment of the subject of optimization, recommended for use by industry professionals, scientists, and students interested in optimization algorithms and their various applications. It provides a complete teaching package with MATLAB exercises and online solutions to end-of-chapter problems.

describes the details of cloud migration, the crucial role of monitoring in optimizing the cloud, and the basics of disaster recovery using cloud infrastructure. This technically rigorous yet simple-to-follow textbook is an ideal resource for graduate courses on cloud computing.

This comprehensive Guide to Web Development with Java introduces the readers to the three-tiered, Model-View-Controller architecture by using Spring JPA, JSPs, and Spring MVC controllers. These three technologies use Java, so that a student with a background in programming will be able to master them with ease, with the end result of being able to create web applications that use MVC, validate user input,and save data to a database.Topics and features:¿ Presents web development topics in an accessible, easy-to-follow style, focusing on core information first, and allowing the reader to gain basic understanding before moving forwards¿ Contains many helpful pedagogical tools for students and lecturers, such as questions and exercises at the end of each chapter, detailed illustrations, chapter summaries, and a glossary¿ Uses existing powerful technologies that are freely available on the web to speedup web development, such as Spring Boot, Spring MVC, Spring JPA, Hibernate, JSP, JSTL, and Java 1.8¿ Discusses HTML, HTML forms, and Cascading Style Sheets¿ Starts with the simplest technology for web development (JSP) and gradually introduces the reader to more complex topics¿ Introduces core technologies from the outset, such as the Model-View-Controller architecture¿ Includes examples for accessing common web services¿ Provides supplementary examples and tutorials

This book presents a broad overview of computer graphics (CG), its history, and the hardware tools it employs. examines advanced techniques in CG, including the nature and properties of light and color, graphics standards and file formats, and fractals;

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of ΓÇ£recipes,ΓÇ¥ this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projectsIncludes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decadeProvides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and softwareSuitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

This practically-focused study guide introduces the fundamentals of discrete mathematics through an extensive set of classroom-tested problems. Each chapter presents a concise introduction to the relevant theory, followed by a detailed account of common challenges and methods for overcoming these. The reader is then encouraged to practice solving such problems for themselves, by tackling a varied selection of questions and assignments of different levels of complexity.This updated second edition now covers the design and analysis of algorithms using Python, and features more than 50 new problems, complete with solutions.Topics and features: provides a substantial collection of problems and examples of varying levels of difficulty, suitable for both laboratory practical training and self-study; offers detailed solutions to each problem, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including Turing machines, asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus.This hands-on workbook is an invaluable resource for undergraduate students of computer science, informatics, and electronic engineering. Suitable for use in a one- or two-semester course on discrete mathematics, the text emphasizes the skills required to develop and implement an algorithm in a specific programming language.

This effective introduction to the key concepts in computational social science includes formal definitions and a glossary, covers topics such as information extraction, social networks and complexity theory, and discusses a range of methodological tools.

explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability;

This classroom-tested book discusses artificial neural networks, evolutionary algorithms, fuzzy systems and Bayesian networks, covering ant colony optimization and probabilistic graphical models. Includes examples, illustrations and definitions throughout.

In its revised and updated edition, this book now offers coverage of such multimedia topics as 3D TV, social networks, high-efficiency video compression and conferencing, wireless and mobile networks and their attendant technologies. Includes study exercises.

This text covers the state of the art in multivariate algorithmics and complexity, a vital field with countless applications in modern computing. It describes the latest methods of proving parameterized tractability, including powerful lower-bound techniques.

This book presents a novel approach to database concepts, describing a categorical logic for database schema mapping based on views, within a framework for database integration and exchange and peer-to-peer computing. Includes practical examples.

The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing.

This comprehensive book covers the fundamental concepts of formal languages and compilation. It presents the subject in a minimalist way, using illustrated examples throughout and providing pedagogical tools, such as slides for lecturers via website.

This book describes the key concepts, principles and implementation options for creating high-assurance cloud computing solutions, beginning with a broad technical overview, and moving through the challenges of reliability and fault-tolerance.