Bøger i Undergraduate Topics in Computer Science serien

This illuminating textbook provides a concise review of the core concepts in mathematics essential to computer scientists. Emphasis is placed on the practical computing applications enabled by seemingly abstract mathematical ideas, presented within their historical context. The text spans a broad selection of key topics, ranging from the use of finite field theory to correct code and the role of number theory in cryptography, to the value of graph theory when modelling networks and the importance of formal methods for safety critical systems.This fully updated new edition has been expanded with a more comprehensive treatment of algorithms, logic, automata theory, model checking, software reliability and dependability, algebra, sequences and series, and mathematical induction.Topics and features: includes numerous pedagogical features, such as chapter-opening key topics, chapter introductions and summaries, review questions, and a glossary; describes the historical contributions of such prominent figures as Leibniz, Babbage, Boole, and von Neumann; introduces the fundamental mathematical concepts of sets, relations and functions, along with the basics of number theory, algebra, algorithms, and matrices; explores arithmetic and geometric sequences and series, mathematical induction and recursion, graph theory, computability and decidability, and automata theory; reviews the core issues of coding theory, language theory, software engineering, and software reliability, as well as formal methods and model checking; covers key topics on logic, from ancient Greek contributions to modern applications in AI, and discusses the nature of mathematical proof and theorem proving; presents a short introduction to probability and statistics, complex numbers and quaternions, and calculus.This engaging and easy-to-understand book will appeal to students of computer science wishing for an overview of the mathematics used in computing, and to mathematicianscurious about how their subject is applied in the field of computer science. The book will also capture the interest of the motivated general reader.

This practically-focused textbook provides a concise and accessible introduction to the field of software testing, explaining the fundamental principles and offering guidance on applying the theory in an industrial environment.Topics and features: presents a brief history of software quality and its influential pioneers, as well as a discussion of the various software lifecycles used in software development; describes the fundamentals of testing in traditional software engineering, and the role that static testing plays in building quality into a product; explains the process of software test planning, test analysis and design, and test management; discusses test outsourcing, and test metrics and problem solving; reviews the tools available to support software testing activities, and the benefits of a software process improvement initiative; examines testing in the Agile world, and the verification of safety critical systems; considers the legal and ethical aspects of software testing, and the importance of software configuration management; provides key learning topics and review questions in every chapter, and supplies a helpful glossary at the end of the book.This easy-to-follow guide is an essential resource for undergraduate students of computer science seeking to learn about software testing, and how to build high quality and reliable software on time and on budget. The work will also be of interest to industrialists including software engineers, software testers, quality professionals and software managers, as well as the motivated general reader.

Advanced Guide to Python 3 Programming delves deeply into a host of subjects that you need to understand if you are to develop sophisticated real-world programs. Each topic is preceded by an introduction followed by more advanced topics, along with numerous examples, that take you to an advanced level. There are nine different sections within the book covering Computer Graphics (including GUIs), Games, Testing, File Input and Output, Databases Access, Logging, Concurrency and Parallelism, Reactive programming, and Networking. Each section is self-contained and can either be read on its own or as part of the book as a whole. This book is aimed at the those who have learnt the basics of the Python 3 language but want to delve deeper into Python¿s eco system of additional libraries and modules, to explore concurrency and parallelism, to create impressive looking graphical interfaces, to work with databases and files and to provide professional logging facilities.

This engaging textbook provides an accessible introduction to coding and the world of Object-Oriented (OO) programming, using Java as the illustrative programming language.

In this textbook the authors introduce the important concepts of the financial software domain, and motivate the use of an agile software engineering approach for the development of financial software. They describe the role of software in defining financial models and in computing results from these models. Practical examples from bond pricing, yield curve estimation, share price analysis and valuation of derivative securities are given to illustrate the process of financial software engineering.Financial Software Engineering also includes a number of case studies based on typical financial engineering problems:*Internal rate of return calculation for bonds* Macaulay duration calculation for bonds* Bootstrapping of interest rates* Estimation of share price volatility* Technical analysis of share prices* Re-engineering Matlab to C#* Yield curve estimation* Derivative security pricing* Risk analysis of CDOs The book is suitable for undergraduate and postgraduate study, and for practitioners who wish to extend their knowledge of software engineering techniques for financial applications

This practically-focused textbook presents a concise tutorial on data structures and algorithms using the object-functional language Scala.

This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of mathematically supported insights into the methods and relations between them. Two Chapters describe methods for categorical summarization: partitioning, divisive clustering and separate cluster finding and another explain the methods for quantitative summarization, Principal Component Analysis and PageRank. Features:· An in-depth presentation of K-means partitioning including a corresponding Pythagorean decomposition of the data scatter. · Advice regarding such issues as clustering of categorical and mixed scale data, similarity and network data, interpretation aids, anomalous clusters, the number of clusters, etc.· Thorough attention to data-driven modelling including a number of mathematically stated relations between statistical and geometrical concepts including those between goodness-of-fit criteria for decision trees and data standardization, similarity and consensus clustering, modularity clustering and uniform partitioning.New edition highlights: · Inclusion of ranking issues such as Google PageRank, linear stratification and tied rankings median, consensus clustering, semi-average clustering, one-cluster clustering· Restructured to make the logics more straightforward and sections self-containedCore Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field as well as appealing to novices and practitioners.

This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students.

This book is an introduction to the design and implementation of operating systems using OSP 2, the next generation of the highly popular OSP courseware for undergraduate operating system courses. The book allows students to practice these skills in a realistic operating systems programming environment.

This book provides a needed introductory presentation of the fundamental ideas behind these approaches, stresses their relationship by formulating and proving the relevant theorems, and illustrates the applications of semantics in computer science.

This easy-to-follow textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling.

This fully updated second edition also includes new material on virtual machine technologies such as VirtualBox, Vagrant and the Linux container system Docker.Topics and features: presents an overview of the GNU/Linux system, introducing the components of the system, and covering aspects of process management, input/output and environment;

This clearly written textbook presents an accessible introduction to discrete mathematics for computer science students, offering the reader an enjoyable and stimulating path to improve their programming competence. The text empowers students to think critically, to be effective problem solvers, to integrate theory and practice, and to recognize the importance of abstraction. Its motivational and interactive style provokes a conversation with the reader through a questioning commentary, and supplies detailed walkthroughs of several algorithms.This updated and enhanced new edition also includes new material on directed graphs, and on drawing and coloring graphs, in addition to more than 100 new exercises (with solutions to selected exercises).Topics and features: assumes no prior mathematical knowledge, and discusses concepts in programming as and when they are needed; designed for both classroom use and self-study, presenting modular and self-contained chapters that follow ACM curriculum recommendations; describes mathematical processes in an algorithmic manner, often supported by a walkthrough demonstrating how the algorithm performs the desired task; includes an extensive set of exercises throughout the text, together with numerous examples, and shaded boxes highlighting key concepts; selects examples that demonstrate a practical use for the concept in question.Students embarking on the start of their studies of computer science will find this book to be an easy-to-understand and fun-to-read primer, ideal for use in a mathematics course taken concurrently with their first programming course.

This invaluable textbook/reference provides an easy-to-read guide to the fundamentals of formal methods, highlighting the rich applications of formal methods across a diverse range of areas of computing.Topics and features: introduces the key concepts in software engineering, software reliability and dependability, formal methods, and discrete mathematics; presents a short history of logic, from Aristotle¿s syllogistic logic and the logic of the Stoics, through Boole¿s symbolic logic, to Frege¿s work on predicate logic; covers propositional and predicate logic, as well as more advanced topics such as fuzzy logic, temporal logic, intuitionistic logic, undefined values, and the applications of logic to AI; examines the Z specification language, the Vienna Development Method (VDM) and Irish School of VDM, and the unified modelling language (UML); discusses Dijksträs calculus of weakest preconditions, Hoare¿s axiomatic semantics of programming languages, and the classical approachof Parnas and his tabular expressions; provides coverage of automata theory, probability and statistics, model checking, and the nature of proof and theorem proving; reviews a selection of tools available to support the formal methodist, and considers the transfer of formal methods to industry; includes review questions and highlights key topics in every chapter, and supplies a helpful glossary at the end of the book.This stimulating guide provides a broad and accessible overview of formal methods for students of computer science and mathematics curious as to how formal methods are applied to the field of computing.

In doing so it provides readers with a comprehensive understanding of where software quality fits into the development lifecycle (spoiler: everywhere), and what the key quality assurance activities are. The book focuses on quality assurance in a way that typical, more generic software engineering reference books do not.

Overview and Goals The agile approach for software development has been applied more and more extensively since the mid nineties of the 20th century.

This book provides a concise introduction to Pervasive Computing, otherwise known as Internet of Things (IoT) and Ubiquitous Computing (Ubicomp) which addresses the seamless integration of computing systems within everyday objects.

A strong mathematical foundation of the logical engines available in modern proof assistants, such as the PVS verification system, is essential for computer scientists, mathematicians and engineers to increment their capabilities to provide formal proofs of theorems and to certify the robustness of software and hardware systems.

Programming language analysis and translation techniques are used in many software application areas.A Practical Approach to Compiler Construction covers the fundamental principles of the subject in an accessible way.

Focus on issues and principles in context awareness, sensor processing and software design (rather than sensor networks or HCI or particular commercial systems). Designed as a textbook, with readings and lab problems in most chapters. Focus on concepts, algorithms and ideas rather than particular technologies.

This concise and accessible textbook will enable readers to quickly develop the working skills necessary to solve computational problems in a server-based environment, using HTML and PHP. The importance of learning by example (as opposed to simply learning by copying) is emphasized through extensive use of hands-on exercises and examples, with a specific focus on useful science and engineering applications. The clearly-written text is designed to be simple to follow for the novice student, without requiring any background in programming or mathematics beyond algebra.Topics and features: describes the creation of HTML pages and the characteristics of HTML documents, showing how to use HTML tables, forms, lists, and frames to organize documents for use with PHP applications; explains how to set up a PHP environment, using a local or remote server; introduces the capabilities and syntax of the PHP language, including coverage of array syntax and use; examines user-defined functionsin programming, summarizing PHP functions for reading and writing files, viewing the content of variables, and manipulating strings; reviews the PHP GD graphics library, presenting applications for creating pie charts, bar graphs, and line graphs suitable for displaying scientific data; includes appendices listing HTML and ASCII special characters, and highlighting the essential basic strategies for solving computational problems.Supplying all of the tools necessary to begin coding in HTML and PHP, this invaluable textbook is ideal for undergraduate students taking introductory courses in programming. The book will also serve as a helpful self-study text for professionals in any technical field.

The other describes how to compile a C subset to real (x86) hardware, as a smooth extension of the previously presented compilers.The examples present several interpreters and compilers for toy languages, including compilers for a small but usable subset of C, abstract machines, a garbage collector, and ML-style polymorphic type inference.

Tracing the story of computing from Babylonian counting boards to smartphones, this inspiring textbook provides a concise overview of the key events in the history of computing, together with discussion exercises to stimulate deeper investigation into this fascinating area.