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| domains in computer science: Domain Science and Engineering Dines Bjørner, 2021-11-08 In this book the author explains domain engineering and the underlying science, and he then shows how we can derive requirements prescriptions for computing systems from domain descriptions. A further motivation is to present domain descriptions, requirements prescriptions, and software design specifications as mathematical quantities. The author's maxim is that before software can be designed we must understand its requirements, and before requirements can be prescribed we must analyse and describe the domain for which the software is intended. He does this by focusing on what it takes to analyse and describe domains. By a domain we understand a rationally describable discrete dynamics segment of human activity, of natural and man-made artefacts, examples include road, rail and air transport, container terminal ports, manufacturing, trade, healthcare, and urban planning. The book addresses issues of seemingly large systems, not small algorithms, and it emphasizes descriptions as formal, mathematical quantities. This is the first thorough monograph treatment of the new software engineering phase of software development, one that precedes requirements engineering. It emphasizes a methodological approach by treating, in depth, analysis and description principles, techniques and tools. It does this by basing its domain modeling on fundamental philosophical principles, a view that is new for a computer science monograph. The book will be of value to computer scientists engaged with formal specifications of software. The author reveals this as a field of interesting problems, most chapters include pointers to further study and exercises drawn from practical engineering and science challenges. The text is supported by a primer to the formal specification language RSL and extensive indexes. |
| domains in computer science: Mathematical Theory of Domains V. Stoltenberg-Hansen, I. Lindström, E. R. Griffor, 1994-09-22 Introductory textbook/general reference in domain theory for professionals in computer science and logic. |
| domains in computer science: Domains and Lambda-Calculi Roberto M. Amadio, Pierre-Louis Curien, 1998-07-02 Graduate text on mathematical foundations of programming languages, and operational and denotational semantics. |
| domains in computer science: On Computing Paul S. Rosenbloom, 2012-11-09 A proposal that computing is not merely a form of engineering but a scientific domain on a par with the physical, life, and social sciences. Computing is not simply about hardware or software, or calculation or applications. Computing, writes Paul Rosenbloom, is an exciting and diverse, yet remarkably coherent, scientific enterprise that is highly multidisciplinary yet maintains a unique core of its own. In On Computing, Rosenbloom proposes that computing is a great scientific domain on a par with the physical, life, and social sciences. Rosenbloom introduces a relational approach for understanding computing, conceptualizing it in terms of forms of interaction and implementation, to reveal the hidden structures and connections among its disciplines. He argues for the continuing vitality of computing, surveying the leading edge in computing's combination with other domains, from biocomputing and brain-computer interfaces to crowdsourcing and virtual humans to robots and the intermingling of the real and the virtual. He explores forms of higher order coherence, or macrostructures, over complex computing topics and organizations. Finally, he examines the very notion of a great scientific domain in philosophical terms, honing his argument that computing should be considered the fourth great scientific domain. With On Computing, Rosenbloom, a key architect of the founding of University of Southern California's Institute for Creative Technologies and former Deputy Director of USC's Information Sciences Institute, offers a broader perspective on what computing is and what it can become. |
| domains in computer science: Software Engineering 3 Dines Bjørner, 2006-03-09 The final installment in this three-volume set is based on this maxim: Before software can be designed its requirements must be well understood, and before the requirements can be expressed properly the domain of the application must be well understood. The book covers the process from the development of domain descriptions, through the derivation of requirements prescriptions from domain models, to the refinement of requirements into software architectures and component design. |
| domains in computer science: Science Fiction and Computing David L. Ferro, Eric G. Swedin, 2011-09-29 The prevalence of science fiction readership among those who create and program computers is so well-known that it has become a cliche, but the phenomenon has remained largely unexplored by scholars. What role has science fiction played in the actual development of computers and computing? And likewise, how has computing (including the related fields of robotics and artificial intelligence) affected the course of science fiction? The 18 essays in this critical work explore the interrelationship of these domains over the span of more than half a century. |
| domains in computer science: Domain-driven Design Eric Evans, 2004 Domain-Driven Design incorporates numerous examples in Java-case studies taken from actual projects that illustrate the application of domain-driven design to real-world software development. |
| domains in computer science: Domain-Driven Design Reference Eric Evans, 2014-09-22 Domain-Driven Design (DDD) is an approach to software development for complex businesses and other domains. DDD tackles that complexity by focusing the team's attention on knowledge of the domain, picking apart the most tricky, intricate problems with models, and shaping the software around those models. Easier said than done! The techniques of DDD help us approach this systematically. This reference gives a quick and authoritative summary of the key concepts of DDD. It is not meant as a learning introduction to the subject. Eric Evans' original book and a handful of others explain DDD in depth from different perspectives. On the other hand, we often need to scan a topic quickly or get the gist of a particular pattern. That is the purpose of this reference. It is complementary to the more discursive books. The starting point of this text was a set of excerpts from the original book by Eric Evans, Domain-Driven-Design: Tackling Complexity in the Heart of Software, 2004 - in particular, the pattern summaries, which were placed in the Creative Commons by Evans and the publisher, Pearson Education. In this reference, those original summaries have been updated and expanded with new content. The practice and understanding of DDD has not stood still over the past decade, and Evans has taken this chance to document some important refinements. Some of the patterns and definitions have been edited or rewritten by Evans to clarify the original intent. Three patterns have been added, describing concepts whose usefulness and importance has emerged in the intervening years. Also, the sequence and grouping of the topics has been changed significantly to better emphasize the core principles. This is an up-to-date, quick reference to DDD. |
| domains in computer science: Abstract Domains in Constraint Programming Marie Pelleau, 2015-05-20 Constraint Programming aims at solving hard combinatorial problems, with a computation time increasing in practice exponentially. The methods are today efficient enough to solve large industrial problems, in a generic framework. However, solvers are dedicated to a single variable type: integer or real. Solving mixed problems relies on ad hoc transformations. In another field, Abstract Interpretation offers tools to prove program properties, by studying an abstraction of their concrete semantics, that is, the set of possible values of the variables during an execution. Various representations for these abstractions have been proposed. They are called abstract domains. Abstract domains can mix any type of variables, and even represent relations between the variables. In this work, we define abstract domains for Constraint Programming, so as to build a generic solving method, dealing with both integer and real variables. We also study the octagons abstract domain, already defined in Abstract Interpretation. Guiding the search by the octagonal relations, we obtain good results on a continuous benchmark. We also define our solving method using Abstract Interpretation techniques, in order to include existing abstract domains. Our solver, AbSolute, is able to solve mixed problems and use relational domains. - Exploits the over-approximation methods to integrate AI tools in the methods of CP - Exploits the relationships captured to solve continuous problems more effectively - Learn from the developers of a solver capable of handling practically all abstract domains |
| domains in computer science: The Domain Theory Alistair Sutcliffe, A.G. Sutcliffe, 2002-03-01 Is this book about patterns? Yes and no. It is about software reuse and representation of knowledge that can be reapplied in similar situations; however, it does not follow the classic Alexandine conventions of the patterns community--i.e. Problem- solution- forces- context- example, etc. Chapter 6 on claims comes close to classic patterns, and the whole book can be viewed as a patterns language of abstract models for software engineering and HCI. So what sort of patterns does it contain? Specifications, conceptual models, design advice, but sorry not code. Plenty of other C++ code pattern books (see PLOP series). Nearest relative in published patterns books are Fowler's (1995) Analysis Patterns: Reusable object models and Coad, North and Mayfield. What do you mean by a Domain Theory? Not domains in the abstract mathematical sense, but domains in the knowledge--natural language sense, close to the everyday meaning when we talk about the application domain of a computer system, such as car rental, satellite tracking, whatever. The book is an attempt to answer the question ' what are the abstractions behind car rental, satellite tracking' so good design solutions for those problems can be reused. I work in industry, so what's in it for me? A new way of looking at software reuse, ideas for organizing a software and knowledge reuse program, new processes for reusing knowledge in requirements analysis, conceptual modeling and software specification. I am an academic, should I be interested? Yes if your research involves software engineering, reuse, requirements engineering, human computer interaction, knowledge engineering, ontologies and knowledge management. For teaching it may be useful for Master courses on reuse, requirements and knowledge engineering. More generally if you are interested in exploring what the concept of abstraction is when you extend it beyond programming languages, formal specification, abstract data types, etc towards requirements and domain knowledge. ADDITIONAL COPY: Based on more than 10 years of research by the author, this book is about putting software reuse on a firmer footing. Utilizing a multidisciplinary perspective--psychology and management science, as well as software--it describes the Domain Theory as a solution. The domain theory provides an abstract theory that defines a generic, reusable model of domain knowledge. Providing a comprehensive library of reusable models, practice methods for reuse, and theoretical insight, this book: *introduces the subject area of reuse and software engineering and explains a framework for comparing different reuse approaches; *develops a metric-oriented framework to assess the reuse claims of three competing approaches: patterns, ERPs, and the Domain Theory OSMs (object system models); *explains the psychological background for reuse and describes generic tasks and meta-domains; *introduces claims that provide a representation of design knowledge attached to Domain Theory models, as well as being a schema for representing reusable knowledge in nearly any form; *reports research that resulted from the convergence of the two theories; *describes the methods, techniques, and guidelines of design for reuse--the process of abstraction; and *elaborates the framework to investigate the future of reuse by different paradigms, generation of applications from requirements languages, and component-based software engineering via reuse libraries. |
| domains in computer science: Logic of Domains G. Zhang, 2012-12-06 This monograph studies the logical aspects of domains as used in de notational semantics of programming languages. Frameworks of domain logics are introduced; these serve as foundations for systematic derivations of proof systems from denotational semantics of programming languages. Any proof system so derived is guaranteed to agree with denotational se mantics in the sense that the denotation of any program coincides with the set of assertions true of it. The study focuses on two categories for dena tational semantics: SFP domains, and the less standard, but important, category of stable domains. The intended readership of this monograph includes researchers and graduate students interested in the relation between semantics of program ming languages and formal means of reasoning about programs. A basic knowledge of denotational semantics, mathematical logic, general topology, and category theory is helpful for a full understanding of the material. Part I SFP Domains Chapter 1 Introduction This chapter provides a brief exposition to domain theory, denotational se mantics, program logics, and proof systems. It discusses the importance of ideas and results on logic and topology to the understanding of the relation between denotational semantics and program logics. It also describes the motivation for the work presented by this monograph, and how that work fits into a more general program. Finally, it gives a short summary of the results of each chapter. 1. 1 Domain Theory Programming languages are languages with which to perform computa tion. |
| domains in computer science: Law for Computer Scientists and Other Folk Mireille Hildebrandt, 2020 This book introduces law to computer scientists and other folk. Computer scientists develop, protect, and maintain computing systems in the broad sense of that term, whether hardware (a smartphone, a driverless car, a smart energy meter, a laptop, or a server), software (a program, an application programming interface or API, a module, code), or data (captured via cookies, sensors, APIs, or manual input). Computer scientists may be focused on security (e.g. cryptography), or on embedded systems (e.g. the Internet of Things), or on data science (e.g. machine learning). They may be closer to mathematicians or to electrical or electronic engineers, or they may work on the cusp of hardware and software, mathematical proofs and empirical testing. This book conveys the internal logic of legal practice, offering a hands-on introduction to the relevant domains of law, while firmly grounded in legal theory. It bridges the gap between two scientific practices, by presenting a coherent picture of the grammar and vocabulary of law and the rule of law, geared to those with no wish to become lawyers but nevertheless required to consider the salience of legal rights and obligations. Simultaneously, this book will help lawyers to review their own trade. It is a volume on law in an onlife world, presenting a grounded argument of what law does (speech act theory), how it emerged in the context of printed text (philosophy of technology), and how it confronts its new, data-driven environment. Book jacket. |
| domains in computer science: Encyclopedia of Computer Science and Technology Allen Kent, James G. Williams, 1999-05-14 An Approach to Complexity from a Human-Centered Artificial Intelligence Perspective to The Virtual Workplace |
| domains in computer science: Towards Interoperable Research Infrastructures for Environmental and Earth Sciences Zhiming Zhao, Margareta Hellström, 2020-07-24 This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions. |
| domains in computer science: Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification Cong-Vinh, Phan, 2011-10-31 Autonomic computing and networking (ACN), a concept inspired by the human autonomic system, is a priority research area and a booming new paradigm in the field. Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development, and Verification outlines the characteristics, novel approaches of specification, refinement, programming and verification associated with ACN. The goal of ACN and the topics covered in this work include making networks and computers more self-organized, self- configured, self-healing, self-optimizing, self-protecting, and more. This book helpfully details the steps necessary towards realizing computer and network autonomy and its implications. |
| domains in computer science: Coding the Matrix Philip N. Klein, 2013-07 An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by doing, writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code. Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant xkcd comics. Chapters: The Function, The Field, The Vector, The Vector Space, The Matrix, The Basis, Dimension, Gaussian Elimination, The Inner Product, Special Bases, The Singular Value Decomposition, The Eigenvector, The Linear Program A new edition of this text, incorporating corrections and an expanded index, has been issued as of September 4, 2013, and will soon be available on Amazon. |
| domains in computer science: Commonsense Reasoning Erik T. Mueller, 2010-07-26 To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world. - Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states. - The first full book on commonsense reasoning to use the event calculus. - Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall. - Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves. - Includes fully worked out proofs and circumscriptions for every example. |
| domains in computer science: Discovering Computer Science Jessen Havill, 2020-10-12 Havill's problem-driven approach introduces algorithmic concepts in context and motivates students with a wide range of interests and backgrounds. -- Janet Davis, Associate Professor and Microsoft Chair of Computer Science, Whitman College This book looks really great and takes exactly the approach I think should be used for a CS 1 course. I think it really fills a need in the textbook landscape. -- Marie desJardins, Dean of the College of Organizational, Computational, and Information Sciences, Simmons University Discovering Computer Science is a refreshing departure from introductory programming texts, offering students a much more sincere introduction to the breadth and complexity of this ever-growing field. -- James Deverick, Senior Lecturer, The College of William and Mary This unique introduction to the science of computing guides students through broad and universal approaches to problem solving in a variety of contexts and their ultimate implementation as computer programs. -- Daniel Kaplan, DeWitt Wallace Professor, Macalester College Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming is a problem-oriented introduction to computational problem solving and programming in Python, appropriate for a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience. Realizing that an organization around language features only resonates with a narrow audience, this textbook instead connects programming to students’ prior interests using a range of authentic problems from the natural and social sciences and the digital humanities. The presentation begins with an introduction to the problem-solving process, contextualizing programming as an essential component. Then, as the book progresses, each chapter guides students through solutions to increasingly complex problems, using a spiral approach to introduce Python language features. The text also places programming in the context of fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, offering glimpses of topics that are traditionally put off until later courses. This book contains 30 well-developed independent projects that encourage students to explore questions across disciplinary boundaries, over 750 homework exercises, and 300 integrated reflection questions engage students in problem solving and active reading. The accompanying website — https://www.discoveringcs.net — includes more advanced content, solutions to selected exercises, sample code and data files, and pointers for further exploration. |
| domains in computer science: Representation Theorems in Computer Science Özgür Lütfü Özçep, 2019-07-16 Formal specifications are an important tool for the construction, verification and analysis of systems, since without it is hardly possible to explain whether a system worked correctly or showed an expected behavior. This book proposes the use of representation theorems as a means to develop an understanding of all models of a specification in order to exclude possible unintended models, demonstrating the general methodology with representation theorems for applications in qualitative spatial reasoning, data stream processing, and belief revision. For qualitative spatial reasoning, it develops a model of spatial relatedness that captures the scaling context with hierarchical partitions of a spatial domain, and axiomatically characterizes the resulting relations. It also shows that various important properties of stream processing, such as prefix-determinedness or various factorization properties can be axiomatized, and that the axioms are fulfilled by natural classes of stream functions. The third example is belief revision, which is concerned with the revision of knowledge bases under new, potentially incompatible information. In this context, the book considers a subclass of revision operators, namely the class of reinterpretation operators, and characterizes them axiomatically. A characteristic property of reinterpretation operators is that of dissolving potential inconsistencies by reinterpreting symbols of the knowledge base. Intended for researchers in theoretical computer science or one of the above application domains, the book presents results that demonstrate the use of representation theorems for the design and evaluation of formal specifications, and provide the basis for future application-development kits that support application designers with automatically built representations. |
| domains in computer science: Computer Science Logo Style Brian Harvey, 1997 |
| domains in computer science: Advanced CISSP Prep Guide Ronald L. Krutz, Russell Dean Vines, 2003-02-03 Get ready to pass the CISSP exam and earn your certification with this advanced test guide Used alone or as an in-depth supplement to the bestselling The CISSP Prep Guide, this book provides you with an even more intensive preparation for the CISSP exam. With the help of more than 300 advanced questions and detailed answers, you'll gain a better understanding of the key concepts associated with the ten domains of the common body of knowledge (CBK). Each question is designed to test you on the information you'll need to know in order to pass the exam. Along with explanations of the answers to these advanced questions, you'll find discussions on some common incorrect responses as well. In addition to serving as an excellent tutorial, this book presents you with the latest developments in information security. It includes new information on: Carnivore, Echelon, and the U.S. Patriot Act The Digital Millennium Copyright Act (DMCA) and recent rulings The European Union Electronic Signature Directive The Advanced Encryption Standard, biometrics, and the Software Capability Maturity Model Genetic algorithms and wireless security models New threats and countermeasures The CD-ROM includes all the questions and answers from the book with the Boson-powered test engine. |
| domains in computer science: Signposts in Cyberspace National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Internet Navigation and the Domain Name System: Technical Alternatives and Policy Implications, 2005-08-07 The Domain Name System (DNS) enables user-friendly alphanumeric namesâ€domain namesâ€to be assigned to Internet sites. Many of these names have gained economic, social, and political value, leading to conflicts over their ownership, especially names containing trademarked terms. Congress, in P.L. 105-305, directed the Department of Commerce to request the NRC to perform a study of these issues. When the study was initiated, steps were already underway to address the resolution of domain name conflicts, but the continued rapid expansion of the use of the Internet had raised a number of additional policy and technical issues. Furthermore, it became clear that the introduction of search engines and other tools for Internet navigation was affecting the DNS. Consequently, the study was expanded to include policy and technical issues related to the DNS in the context of Internet navigation. This report presents the NRC's assessment of the current state and future prospects of the DNS and Internet navigation, and its conclusions and recommendations concerning key technical and policy issues. |
| domains in computer science: Knowledge Driven Development Manoj Kumar Lal, 2018-07-12 Provides detailed methodology for digitizing project knowledge by bridging the gap between Waterfall and Agile Methodologies. |
| domains in computer science: Domain-Specific Languages Martin Fowler, 2010-09-23 When carefully selected and used, Domain-Specific Languages (DSLs) may simplify complex code, promote effective communication with customers, improve productivity, and unclog development bottlenecks. In Domain-Specific Languages, noted software development expert Martin Fowler first provides the information software professionals need to decide if and when to utilize DSLs. Then, where DSLs prove suitable, Fowler presents effective techniques for building them, and guides software engineers in choosing the right approaches for their applications. This book’s techniques may be utilized with most modern object-oriented languages; the author provides numerous examples in Java and C#, as well as selected examples in Ruby. Wherever possible, chapters are organized to be self-standing, and most reference topics are presented in a familiar patterns format. Armed with this wide-ranging book, developers will have the knowledge they need to make important decisions about DSLs—and, where appropriate, gain the significant technical and business benefits they offer. The topics covered include: How DSLs compare to frameworks and libraries, and when those alternatives are sufficient Using parsers and parser generators, and parsing external DSLs Understanding, comparing, and choosing DSL language constructs Determining whether to use code generation, and comparing code generation strategies Previewing new language workbench tools for creating DSLs |
| domains in computer science: Algorithms and Data Structures for External Memory Jeffrey Scott Vitter, 2008 Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing. |
| domains in computer science: Semantics with Applications: An Appetizer Hanne Riis Nielson, Flemming Nielson, 2007-04-18 Semantics will play an important role in the future development of software systems and domain-specific languages. 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. Historically important application areas are presented together with some exciting potential applications. The text investigates the relationship between various methods and describes some of the main ideas used, illustrating these by means of interesting applications. The book provides a rigorous introduction to the main approaches to formal semantics of programming languages. |
| domains in computer science: Domains and Processes Klaus Keimel, Guo-Qiang Zhang, Ying Ming Liu, Yixiang Chen, 2012-12-06 Domain theory is a rich interdisciplinary area at the intersection of logic, computer science, and mathematics. This volume contains selected papers presented at the International Symposium on Domain Theory which took place in Shanghai in October 1999. Topics of papers range from the encounters between topology and domain theory, sober spaces, Lawson topology, real number computability and continuous functionals to fuzzy modelling, logic programming, and pi-calculi. This book is a valuable reference for researchers and students interested in this rapidly developing area of theoretical computer science. |
| domains in computer science: Computer Science Robert Sedgewick, Kevin Wayne, 2016-06-17 Named a Notable Book in the 21st Annual Best of Computing list by the ACM! Robert Sedgewick and Kevin Wayne’s Computer Science: An Interdisciplinary Approach is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing. The book demystifies computation, explains its intellectual underpinnings, and covers the essential elements of programming and computational problem solving in today’s environments. The authors begin by introducing basic programming elements such as variables, conditionals, loops, arrays, and I/O. Next, they turn to functions, introducing key modular programming concepts, including components and reuse. They present a modern introduction to object-oriented programming, covering current programming paradigms and approaches to data abstraction. Building on this foundation, Sedgewick and Wayne widen their focus to the broader discipline of computer science. They introduce classical sorting and searching algorithms, fundamental data structures and their application, and scientific techniques for assessing an implementation’s performance. Using abstract models, readers learn to answer basic questions about computation, gaining insight for practical application. Finally, the authors show how machine architecture links the theory of computing to real computers, and to the field’s history and evolution. For each concept, the authors present all the information readers need to build confidence, together with examples that solve intriguing problems. Each chapter contains question-and-answer sections, self-study drills, and challenging problems that demand creative solutions. Companion web site (introcs.cs.princeton.edu/java) contains Extensive supplementary information, including suggested approaches to programming assignments, checklists, and FAQs Graphics and sound libraries Links to program code and test data Solutions to selected exercises Chapter summaries Detailed instructions for installing a Java programming environment Detailed problem sets and projects Companion 20-part series of video lectures is available at informit.com/title/9780134493831 |
| domains in computer science: Software Architecture for Big Data and the Cloud Ivan Mistrik, Rami Bahsoon, Nour Ali, Maritta Heisel, Bruce Maxim, 2017-06-12 Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. - Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques - Presents case studies involving enterprise, business, and government service deployment of big data applications - Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data |
| domains in computer science: Dynamic Knowledge Representation in Scientific Domains Cyril Pshenichny, Paolo Diviacco, Dmitry Mouromtsev, 2017-12-15 This book focuses on the IT field from the outlook of industry professionals and covers multidisciplinary themes such as human resource management, sociology, psychology, and management along with technology itself. It links theory with application or critically analyzing cases with the objective of identifying good practice in the management of IT human capital-- |
| domains in computer science: Professor Astro Cat's Atomic Adventure Dr. Dominic Walliman, 2016-05-10 Class is in session, and the subject is physics. Your teacher? Why, he’s the smartest cat in the galaxy! In this brilliant follow up to Professor Astro Cat’s Frontiers of Space, our trusty feline returns to take you on a journey through the incredible world of physics. Learn about energy, power and the building blocks of you, me and the universe in this all new ATOMIC ADVENTURE! |
| domains in computer science: Computer Vision -- ECCV 2010 Kostas Daniilidis, Petros Maragos, Nikos Paragios, 2010-08-30 The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis. |
| domains in computer science: The Cambridge Handbook of Computing Education Research Sally A. Fincher, Anthony V. Robins, 2019-02-13 This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry. |
| domains in computer science: Continuous Lattices and Domains G. Gierz, K. H. Hofmann, K. Keimel, J. D. Lawson, M. Mislove, D. S. Scott, 2003-03-06 Table of contents |
| domains in computer science: Drive Daniel H. Pink, 2011-04-05 The New York Times bestseller that gives readers a paradigm-shattering new way to think about motivation from the author of When: The Scientific Secrets of Perfect Timing Most people believe that the best way to motivate is with rewards like money—the carrot-and-stick approach. That's a mistake, says Daniel H. Pink (author of To Sell Is Human: The Surprising Truth About Motivating Others). In this provocative and persuasive new book, he asserts that the secret to high performance and satisfaction-at work, at school, and at home—is the deeply human need to direct our own lives, to learn and create new things, and to do better by ourselves and our world. Drawing on four decades of scientific research on human motivation, Pink exposes the mismatch between what science knows and what business does—and how that affects every aspect of life. He examines the three elements of true motivation—autonomy, mastery, and purpose-and offers smart and surprising techniques for putting these into action in a unique book that will change how we think and transform how we live. |
| domains in computer science: Second International Conference on Image Processing and Capsule Networks Joy Iong-Zong Chen, João Manuel R. S. Tavares, Abdullah M. Iliyasu, Ke-Lin Du, 2021-09-09 This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking. |
| domains in computer science: Domain-Specific Modeling Steven Kelly, Juha-Pekka Tolvanen, 2008-04-11 [The authors] are pioneers. . . . Few in our industry have their breadth of knowledge and experience. —From the Foreword by Dave Thomas, Bedarra Labs Domain-Specific Modeling (DSM) is the latest approach to software development, promising to greatly increase the speed and ease of software creation. Early adopters of DSM have been enjoying productivity increases of 500–1000% in production for over a decade. This book introduces DSM and offers examples from various fields to illustrate to experienced developers how DSM can improve software development in their teams. Two authorities in the field explain what DSM is, why it works, and how to successfully create and use a DSM solution to improve productivity and quality. Divided into four parts, the book covers: background and motivation; fundamentals; in-depth examples; and creating DSM solutions. There is an emphasis throughout the book on practical guidelines for implementing DSM, including how to identify the necessary language constructs, how to generate full code from models, and how to provide tool support for a new DSM language. The example cases described in the book are available the book's Website, www.dsmbook.com, along with, an evaluation copy of the MetaEdit+ tool (for Windows, Mac OS X, and Linux), which allows readers to examine and try out the modeling languages and code generators. Domain-Specific Modeling is an essential reference for lead developers, software engineers, architects, methodologists, and technical managers who want to learn how to create a DSM solution and successfully put it into practice. |
| domains in computer science: Implementing Domain-driven Design Vaughn Vernon, 2013 Vaughn Vernon presents concrete and realistic domain-driven design (DDD) techniques through examples from familiar domains, such as a Scrum-based project management application that integrates with a collaboration suite and security provider. Each principle is backed up by realistic Java examples, and all content is tied together by a single case study of a company charged with delivering a set of advanced software systems with DDD. |
| domains in computer science: Computer Science – Theory and Applications Rahul Santhanam, Daniil Musatov, 2021-06-17 This book constitutes the proceedings of the 16th International Computer Science Symposium in Russia, CSR 2021, held in Sochi, Russia, in June/July 2021. The 28 full papers were carefully reviewed and selected from 68 submissions. The papers cover a broad range of topics, such as formal languages and automata theory, geometry and discrete structures; theory and algorithms for application domains and much more. |
| domains in computer science: System Engineering for IMS Networks Arun Handa, 2009-03-12 The IMS is the foundation architecture for the next generation of mobile phones, wireless-enabled PDAs, PCs, and the like. IMS delivers multimedia content (audio, video, text, etc.) over all types of networks. For network engineers/administrators and telecommunications engineers it will be essential to not only understand IMS architecture, but to also be able to apply it at every stage of the network design process. This book will contain pragmatic information on how to engineer IMS networks as well as an applications-oriented approach for the engineering and networking professionals responsible for making IMS function in the real world. - Describes the convergence of wireless IMS (IP Multimedia Subsystem) with other networks, including wireline and cable - Discusses building interfaces for end users and IMS applications servers - Explores network management issues with IMS |
CS221 Practice Midterm - Stanford University
(4 pts): Formulate this problem as a CSP problem in which there is one variable per class, stating the domains, and constraints. Constraints should be specified formally and precisely, but may …
Domain Engineering - DTU
Before require-ments can be expressed we must understand the domain. So it follows, from our dogma, that we must first establish precise descriptions of domains; then, from such …
Multi-Domain Learning: When Do Domains Matter? - CMU …
We present a systematic analysis of exist-ing multi-domain learning approaches with re-spect to two questions. First, many multi-domain learning algorithms resemble ensem-ble learning …
Domain Theory - Department of Computer Science, University …
1. Domains as types. The fact that suitable categories of domains are cartesian closed, and hence give rise to models of typed ‚-calculi. More generally, that domains give mathematical meaning …
Software Architecture - University of Colorado Boulder …
• domains Lecture 27 3 Software Architecture • The principled study of software components, including their properties, relationships, and patterns of combination • Also, a particular set of …
5 Examples of Prioritised Competence Domains for Computer …
Domains for Computer Science Education As already shown in sections 3.4 and 4.3, competencies can only be acquired in specific contextualised learning situations in which …
Domain Engineering: A Conceptual Model of the Software …
In this paper we outline the basic facets of objectization from domains. Domain, SubDomain, CoDomain, Ethnography, Heurist ics, Brainstorming, Composition, Segmentation, …
Ontology-based representation and design of subject …
This paper presents an ontological approach for representing and designing subject domains in computer science education. An ontology schema is proposed to formally describe the key …
SEMANTIC DOMAINS Dept. of Computer Science, Carnegie …
DOMAINS b y C. A. Gun ter Dept. of Computer and Information Sciences, Univ. P ennsylv ania, Philadelphi a, P A 19104, USA and D. S. Scott Dept. of Computer Science, Carnegie-Mellon …
CompSci356: Computer Network Architectures Lecture 20: …
Each subtree below a node is a DNS domain. Each label can be up to 63 characters long. The total number of characters of a DNS name is limited to 255. There are more than 1000+ top …
Lecture 01: Introduction to Programming Languages
Among the programming domains identified are scientific application, business application, artificial intelligence (AI) applications, systems programming, scripting languages, and hybrid …
The Relevance of Application Domains in Empirical Findings
In this paper we propose a novel definition for software ecosys-tem based on the context, or application domain, that software systems implement in their requirements. We posit that …
Computing Disciplines & Majors - Association for Computing …
Computer science (CS) spans the range from theory through programming to cutting-edge development of computing solutions. Computer science offers a foundation that permits …
Multi-Domain Learning: When Do Domains Matter? - CMU …
this paper is: when do domains matter? Towards this goal we explore two issues. First, we explore the question of whether domain distinc-tions are used by existing MDL algorithms in …
Classification of Domains in Computer Science Using Random …
In this way, the proposed research work has used a supervised machine learning algorithm and random forest on VTT (Video Text Tracks) file of the computer science videos downloaded …
DNS 101 Domain Name Hierarchy - Duke University
Duke University, Department of Computer Science CPS 212: Distributed Information Systems Today 1. Domain Name Service (DNS) illustrates: • issues and structure for large-scale naming …
Multiple Clock Domains - Massachusetts Institute of Technology
Multiple Clock Domains in Bluespec The Clock type, and functions √ Clock families √ Making clocks √ Moving data across clock domains √ Revisit the 802.11a Transmitter ←
Domains In Computer Science (2024) - archive.ncarb.org
Domains In Computer Science: Domain Science and Engineering Dines Bjørner,2021-11-08 In this book the author explains domain engineering and the underlying science and he then …
CS221 Practice Midterm - Stanford University
(4 pts): Formulate this problem as a CSP problem in which there is one variable per class, stating the domains, and constraints. Constraints should be specified formally and precisely, but may …
Domain Engineering - DTU
Before require-ments can be expressed we must understand the domain. So it follows, from our dogma, that we must first establish precise descriptions of domains; then, from such …
Multi-Domain Learning: When Do Domains Matter? - CMU …
We present a systematic analysis of exist-ing multi-domain learning approaches with re-spect to two questions. First, many multi-domain learning algorithms resemble ensem-ble learning …
Domain Theory - Department of Computer Science, …
1. Domains as types. The fact that suitable categories of domains are cartesian closed, and hence give rise to models of typed ‚-calculi. More generally, that domains give mathematical meaning …
Software Architecture - University of Colorado Boulder …
• domains Lecture 27 3 Software Architecture • The principled study of software components, including their properties, relationships, and patterns of combination • Also, a particular set of …
5 Examples of Prioritised Competence Domains for …
Domains for Computer Science Education As already shown in sections 3.4 and 4.3, competencies can only be acquired in specific contextualised learning situations in which …
Domain Engineering: A Conceptual Model of the Software …
In this paper we outline the basic facets of objectization from domains. Domain, SubDomain, CoDomain, Ethnography, Heurist ics, Brainstorming, Composition, Segmentation, …
Ontology-based representation and design of subject …
This paper presents an ontological approach for representing and designing subject domains in computer science education. An ontology schema is proposed to formally describe the key …
SEMANTIC DOMAINS Dept. of Computer Science, Carnegie …
DOMAINS b y C. A. Gun ter Dept. of Computer and Information Sciences, Univ. P ennsylv ania, Philadelphi a, P A 19104, USA and D. S. Scott Dept. of Computer Science, Carnegie-Mellon …
CompSci356: Computer Network Architectures Lecture 20: …
Each subtree below a node is a DNS domain. Each label can be up to 63 characters long. The total number of characters of a DNS name is limited to 255. There are more than 1000+ top …
Lecture 01: Introduction to Programming Languages
Among the programming domains identified are scientific application, business application, artificial intelligence (AI) applications, systems programming, scripting languages, and hybrid …
Domains In Computer Science Copy - archive.ncarb.org
Domains In Computer Science: Domain Science and Engineering Dines Bjørner,2021-11-08 In this book the author explains domain engineering and the underlying science and he then …
The Relevance of Application Domains in Empirical Findings
In this paper we propose a novel definition for software ecosys-tem based on the context, or application domain, that software systems implement in their requirements. We posit that …
Computing Disciplines & Majors - Association for Computing …
Computer science (CS) spans the range from theory through programming to cutting-edge development of computing solutions. Computer science offers a foundation that permits …
Multi-Domain Learning: When Do Domains Matter? - CMU …
this paper is: when do domains matter? Towards this goal we explore two issues. First, we explore the question of whether domain distinc-tions are used by existing MDL algorithms in …
Classification of Domains in Computer Science Using …
In this way, the proposed research work has used a supervised machine learning algorithm and random forest on VTT (Video Text Tracks) file of the computer science videos downloaded …
DNS 101 Domain Name Hierarchy - Duke University
Duke University, Department of Computer Science CPS 212: Distributed Information Systems Today 1. Domain Name Service (DNS) illustrates: • issues and structure for large-scale …
Multiple Clock Domains - Massachusetts Institute of Technology
Multiple Clock Domains in Bluespec The Clock type, and functions √ Clock families √ Making clocks √ Moving data across clock domains √ Revisit the 802.11a Transmitter ←
