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.

Domain engineering is a set of activities intended to develop, maintain, and manage the creation and evolution of an area of knowledge suitable for processing by a range of software systems. It is of considerable practical significance, as it provides methods and techniques that help reduce time-to-market, development costs, and project risks on one hand, and helps improve system quality and performance on a consistent basis on the other. In this book, the editors present a collection of invited chapters from various fields related to domain engineering. The individual chapters present state-of-the-art research and are organized in three parts. The first part focuses on results that deal with domain engineering in software product lines. The second part describes how domain-specific languages are used to support the construction and deployment of domains. Finally, the third part presents contributions dealing with domain engineering within the field of conceptual modeling. All chapters utilize a similar terminology, which will help readers to understand and relate to the chapters content. The book will be especially rewarding for researchers and students of software engineering methodologies in general and of domain engineering and its related fields in particular, as it contains the most comprehensive and up-to-date information on this topic.

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

"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"--

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.

Domain decomposition is an active, interdisciplinary research area that is devoted to the development, analysis and implementation of coupling and decoupling strategies in mathematics, computational science, engineering and industry. A series of international conferences starting in 1987 set the stage for the presentation of many meanwhile classical results on substructuring, block iterative methods, parallel and distributed high performance computing etc. This volume contains a selection from the papers presented at the 15th International Domain Decomposition Conference held in Berlin, Germany, July 17-25, 2003 by the world's leading experts in the field. Its special focus has been on numerical analysis, computational issues,complex heterogeneous problems, industrial problems, and software development.

Software practitioners are rapidly discovering the immense value of Domain-Specific Languages (DSLs) in solving problems within clearly definable problem domains. Developers are applying DSLs to improve productivity and quality in a wide range of areas, such as finance, combat simulation, macro scripting, image generation, and more. But until now, there have been few practical resources that explain how DSLs work and how to construct them for optimal use. Software Language Engineering fills that need. Written by expert DSL consultant Anneke Kleppe, this is the first comprehensive guide to successful DSL design. Kleppe systematically introduces and explains every ingredient of an effective language specification, including its description of concepts, how those concepts are denoted, and what those concepts mean in relation to the problem domain. Kleppe carefully illuminates good design strategy, showing how to maximize the flexibility of the languages you create. She also demonstrates powerful techniques for creating new DSLs that cooperate well with general-purpose languages and leverage their power. Completely tool-independent, this book can serve as the primary resource for readers using Microsoft DSL tools, the Eclipse Modeling Framework, openArchitectureWare, or any other DSL toolset. It contains multiple examples, an illustrative running case study, and insights and background information drawn from Kleppe’s leading-edge work as a DSL researcher. Specific topics covered include Discovering the types of problems that DSLs can solve, and when to use them Comparing DSLs with general-purpose languages, frameworks, APIs, and other approaches Understanding the roles and tools available to language users and engineers Creating each component of a DSL specification Modeling both concrete and abstract syntax Understanding and describing language semantics Defining textual and visual languages based on object-oriented metamodeling and graph transformations Using metamodels and associated tools to generate grammars Integrating object-oriented modeling with graph theory Building code generators for new languages Supporting multilanguage models and programs This book provides software engineers with all the guidance they need to create DSLs that solve real problems more rapidly, and with higher-quality code.