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This easy-to-follow textbook provides a modern, algorithmic introduction to digital image processing. It concentrates on practical applications and working implementations whilst also presenting important formal details and the necessary mathematics.

Programming Languages is a self-contained approach to the topic, and differentiates between the design, implementation and pragmatic aspects of programming languages overall. The main programming paradigms are presented, in a straightforward way.

The third edition of this textbook has been fully revised and adds material about the SSA form, polymorphism, garbage collection, and pattern matching. It presents techniques for making realistic compilers for simple to intermediate-complexity programming languages. The techniques presented in the book are close to those used in professional compilers, albeit in places slightly simplified for presentation purposes. "Further reading" sections point to material about the full versions of the techniques.All phases required for translating a high-level language to symbolic machine language are covered, and some techniques for optimising code are presented. Type checking and interpretation are also included.Aiming to be neutral with respect to implementation languages, algorithms are mostly presented in pseudo code rather than in any specific language, but suggestions are in many places given for how these can be realised in different language paradigms.Depending on how much of the material from the book is used, it is suitable for both undergraduate and graduate courses for introducing compiler design and implementation.

This unique, accessible textbook gives a comprehensive introduction to software architecture, using ¿clean architecture¿ concepts with agile methods and model-driven development. The work introduces the key concepts of software architectures and explains the importance of architectural design for the long-term usefulness and sustainability of software systems. In addition, it describes more than 30 architectural styles and patterns that can be used for constructing mobile applications, enterprise and web applications, machine-learning systems, and safety-critical systems.Topics and features:Combines clean-architecture principles with agile model-driven developmentEmploys practical examples and real industrial cases to illustrate architectures for mobile apps, web apps, enterprise systems, safety-critical systems and machine-learning systemsExplores support tools for architectural design and system development using the approachProvides tutorial questions and slides to support teaching and learningDelivers material that has been class-tested over 10 years with more than 1,000 studentsThe textbook can be used to support teaching of an undergraduate module in software architecture, yet also includes more advanced topics suitable for a specialised software architecture module at master¿s level. It also will be eminently suitable and relevant for software practitioners and researchers needing or wanting to explore the field in short courses or self-study.Dr. Kevin Lano is Reader in Software Engineering, Department of Informatics, King's College London, UK. Dr. Sobhan Yassipour Tehrani is a Lecturer, Department of Computer Science, University College London, UK.

This textbook presents a focused and accessible primer on the fundamentals of Java programming, with extensive use of illustrative examples and hands-on exercises.Addressing the need to acquire a good working model of objects in order to avoid possible misconceptions, the text introduces the core concepts of object-oriented programming at any stage, supported by the use of contour diagrams. Each chapter has one or more complete programs to illustrate the various ideas presented, and to help readers learn how to write programs on their own. Chapter summaries and practical exercises also are included to help the reader to review their progress and practice their skills.This substantially updated second edition has been expanded with additional exercises, and includes new material on bit manipulation and parallel processing.Topics and features:Introduces computing concepts in Chapter 0 for new programmersAdds new chapters on bit-manipulation and parallel processingContains exercises at the end of each chapter with selected answersSupports both text-based and GUI-based Input/OutputObjects can be introduced first, last, or intermixed with other materialUses contour diagrams to illustrate objects and recursionDiscusses OOP concepts such as overloading, class methods, and inheritanceIntroduces string variables and illustrates arrays and array processingDiscusses files, elementary exception processing, and the basics of JavadocThis concise and easy-to-follow textbook/guide is ideal for students in an introductory programming course. It is also suitable as a self-study guide for both practitioners and academics.

Data privacy technologies are essential for implementing information systems with privacy by design.Privacy technologies clearly are needed for ensuring that data does not lead to disclosure, but also that statistics or even data-driven machine learning models do not lead to disclosure.  For example, can a deep-learning model be attacked to discover that sensitive data has been used for its training?  This accessible textbook presents privacy models, computational definitions of privacy, and methods to implement them. Additionally, the book explains and gives plentiful examples of how to implement-among other models-differential privacy, k-anonymity, and secure multiparty computation.Topics and features:Provides integrated presentation of data privacy (including tools from statistical disclosure control, privacy-preserving data mining, and privacy for communications)Discusses privacy requirements and tools for different types of scenarios, including privacy for data, for computations, and for usersOffers characterization of privacy models, comparing their differences, advantages, and disadvantagesDescribes some of the most relevant algorithms to implement privacy modelsIncludes examples of data protection mechanismsThis unique textbook/guide contains numerous examples and succinctly and comprehensively gathers the relevant information. As such, it will be eminently suitable for undergraduate and graduate students interested in data privacy, as well as professionals wanting a concise overview.Vicenc Torra is Professor with the Department of Computing Science at Umea University, Umea, Sweden.

Knowledge of automata theory and formal languages is crucial for understanding human-computer interaction, as well as for understanding the various processes that take place when manipulating knowledge if that knowledge is, indeed, expressed as sentences written in a suitably formalized language. In particular, it is at the basis of the theory of parsing, which plays an important role in language translation, compiler construction, and knowledge manipulation in general.Presenting basic notions and fundamental results, this concise textbook is structured on the basis of a correspondence that exists between classes of automata and classes of languages. That correspondence is established by the fact that the recognition and the manipulation of sentences in a given class of languages can be done by an automaton in the corresponding class of automata. Four central chapters center on: finite automata and regular languages; pushdown automata and context-free languages; linear bounded automata and context-sensitive languages; and Turing machines and type 0 languages.  The book also examines decidable and undecidable problems with emphasis on the case for context-free languages.Topics and features:Provides theorems, examples, and exercises to clarify automata-languages correspondencesPresents some fundamental techniques for parsing both regular and context-free languagesClassifies subclasses of decidable problems, avoiding focus on the theory of complexityExamines finite-automata minimalization and characterization of their behavior using regular expressionsIllustrates how to derive grammars of context-free languages in Chomsky and Greibach normal formsOffers supplementary material on counter machines, stack automata, and abstract language familiesThis highly useful, varied text/reference is suitable for undergraduate and graduate courses on automata theory and formal languages, and assumes no prior exposure to these topics nor any training in mathematics or logic.Alberto Pettorossi is professor of theoretical computer science at the University of Rome Tor Vergata, Rome, Italy.

The updated and expanded 4th edition of this book explores mathematical techniques and problem-solving strategies for computer games, animation, virtual reality, CAD and other areas of computer graphics. Includes 120 worked examples and some 270 illustrations.

This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms.

New insight in many scientific and engineering fields is unthinkable without the use of numerical simulations running efficiently on modern computers. The faster we get new results, the bigger and accurate are the problems that we can solve. It is the combination of mathematical ideas plus efficient programming that drives the progress in many disciplines. Future champions in the area thus will have to be qualified in their application domain, they will need a profound understanding of some mathematical ideas, and they need the skills to deliver fast code.The present textbook targets students which have programming skills already and do not shy away from mathematics, though they might be educated in computer science or an application domain. It introduces the basic concepts and ideas behind applied mathematics and parallel programming that we need to write numerical simulations for today¿s multicore workstations. Our intention is not to dive into one particular applicationdomain or to introduce a new programming language ¿ we lay the generic foundations for future courses and projects in the area.The text is written in an accessible style which is easy to digest for students without years and years of mathematics education. It values clarity and intuition over formalism, and uses a simple N-body simulation setup to illustrate basic ideas that are of relevance in various different subdomains of scientific computing. Its primary goal is to make theoretical and paradigmatic ideas accessible to undergraduate students and to bring the fascination of the field across.

Computation, itself a form of calculation, incorporates steps that include arithmetical and non-arithmetical (logical) steps following a specific set of rules (an algorithm).

The main goal of this book is to teach fundamental programming principles to beginners using Julia, one of the fastest growing programming languages today. Chapter 5 formally treats with functions, enabling a (large) program to be broken up into smaller manageable units which work together to solve a given problem.

Cryptography, as done in this century, is heavily mathematical. But it also has roots in what is computationally feasible. This unique textbook text balances the theorems of mathematics against the feasibility of computation. Cryptography is something one actually "does", not a mathematical game one proves theorems about.

Modern businesses depend on data for their very survival, creating a need for sophisticated databases and database technologies to help store, organise and transport their valuable data.This updated and expanded, easy-to-read textbook/reference presents a comprehensive introduction to databases, opening with a concise history of databases and of data as an organisational asset. As relational database management systems are no longer the only database solution, the book takes a wider view of database technology, encompassing big data, NoSQL, object and object-relational, and in-memory databases. Presenting both theoretical and practical elements, the new edition also examines the issues of scalability, availability, performance and security encountered when building and running a database in the real world.Topics and features:Presents review and discussion questions at the end of each chapter, in addition toskill-building, hands-on exercisesProvides new material on database adaptiveness, integration, and efficiency in relation to data growthIntroduces a range of commercial databases and encourages the reader to experiment with these in an associated learning environmentReviews use of a variety of databases in business environments, including numerous examplesDiscusses areas for further research within this fast-moving domainWith its learning-by-doing approach, supported by both theoretical and practical examples, this clearly-structured textbook will be of great value to advanced undergraduate and postgraduate students of computer science, software engineering, and information technology. Practising database professionals and application developers will also find the book an ideal reference that addresses today's business needs.

Preface.- Part I: Fundamentals of Discrete Mathematics.- Logic.- Proofs.- Algorithms.- Set Theory.- Relations and Functions.- Sequences, Induction and Recursion.- Introduction to Number Theory.- Counting and Probability.- Boolean Algebra and Combinational Circuits.- Introduction to the Theory of Computation.- Part II: Graph Theory.- Introduction to Graphs.- Trees and Traversals.- Subgraphs.- Connectivity, Network Flows and Shortest Paths.- Graph Applications.- A:.- Pseudocode Conventions.- Index.

This concise guide is designed to enable the reader to learn how to program in assembly language as quickly as possible. Through a hands-on programming approach, readers will also learn about the architecture of the Intel processor, and the relationship between high-level and low-level languages.This updated second edition has been expanded with additional exercises, and enhanced with new material on floating-point numbers and 64-bit processing.Topics and features: provides guidance on simpli¿ed register usage, simpli¿ed input/output using C-like statements, and the use of high-level control structures; describes the implementation of control structures, without the use of high-level structures, and often with related C program code; illustrates concepts with one or more complete program; presents review summaries in each chapter, together with a variety of exercises, from short-answer questions to programming assignments; covers selection and iteration structures, logic,shift, arithmetic shift, rotate, and stack instructions, procedures and macros, arrays, and strings; includes an introduction to floating-point instructions and 64-bit processing; examines machine language from a discovery perspective, introducing the principles of computer organization.A must-have resource for undergraduate students seeking to learn the fundamentals necessary to begin writing logically correct programs in a minimal amount of time, this work will serve as an ideal textbook for an assembly language course, or as a supplementary text for courses on computer organization and architecture. The presentation assumes prior knowledge of the basics of programming in a high-level language such as C, C++, or Java.

reviews the basic image processing methods for segmenting or enhancing certain features in an image, with a focus on morphology methods for binary images; describes how to change the geometry within an image, how to align two images so that they are as similar as possible, and how to detect lines and paths in images;

This book explains the principal techniques of data mining, for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed examples, with a focus on algorithms rather than mathematical formalism.

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.