Semantic Software Design

With this practical book, architects, CTOs, and CIOs will learn a set of patterns for the practice of architecture, including analysis, documentation, and communication. Author Eben Hewitt shows you how to create holistic and thoughtful technology plans, communicate them clearly, lead people toward the vision, and become a great architect or Chief Architect. This book covers each key aspect of architecture comprehensively, including how to incorporate business architecture, information architecture, data architecture, application (software) architecture together to have the best chance for the system’s success. Get a practical set of proven architecture practices focused on shipping great products using architecture Learn how architecture works effectively with development teams, management, and product management teams through the value chain Find updated special coverage on machine learning architecture Get usable templates to start incorporating into your teams immediately Incorporate business architecture, information architecture, data architecture, and application (software) architecture together

A guide to the application of the theory and practice of computing to develop and maintain software that economically solves real-world problem How to Engineer Software is a practical, how-to guide that explores the concepts and techniques of model-based software engineering using the Unified Modeling Language. The author—a noted expert on the topic—demonstrates how software can be developed and maintained under a true engineering discipline. He describes the relevant software engineering practices that are grounded in Computer Science and Discrete Mathematics. Model-based software engineering uses semantic modeling to reveal as many precise requirements as possible. This approach separates business complexities from technology complexities, and gives developers the most freedom in finding optimal designs and code. The book promotes development scalability through domain partitioning and subdomain partitioning. It also explores software documentation that specifically and intentionally adds value for development and maintenance. This important book: Contains many illustrative examples of model-based software engineering, from semantic model all the way to executable code Explains how to derive verification (acceptance) test cases from a semantic model Describes project estimation, along with alternative software development and maintenance processes Shows how to develop and maintain cost-effective software that solves real-world problems Written for graduate and undergraduate students in software engineering and professionals in the field, How to Engineer Software offers an introduction to applying the theory of computing with practice and judgment in order to economically develop and maintain software.

The Web is growing at an astounding pace surpassing the 8 billion page mark. However, most pages are still designed for human consumption and cannot be processed by machines. This book provides a well-paced introduction to the Semantic Web. It covers a wide range of topics, from new trends (ontologies, rules) to existing technologies (Web Services and software agents) to more formal aspects (logic and inference). It includes: real-world (and complete) examples of the application of Semantic Web concepts; how the technology presented and discussed throughout the book can be extended to other application areas.

Over the last decade, ontology has become an important modeling component in software engineering. Semantic Web Enabled Software Engineering presents some critical findings on opening a new direction of the research of Software Engineering, by exploiting Semantic Web technologies. Most of these findings are from selected papers from the Semantic Web Enabled Software Engineering (SWESE) series of workshops starting from 2005. Edited by two leading researchers, this advanced text presents a unifying and contemporary perspective on the field. The book integrates in one volume a unified perspective on concepts and theories of connecting Software Engineering and Semantic Web. It presents state-of-the-art techniques on how to use Semantic Web technologies in Software Engineering and introduces techniques on how to design ontologies for Software Engineering.

The next enterprise computing era will rely on the synergy between both technologies: semantic web and model-driven software development (MDSD). The semantic web organizes system knowledge in conceptual domains according to its meaning. It addresses various enterprise computing needs by identifying, abstracting and rationalizing commonalities, and checking for inconsistencies across system specifications. On the other side, model-driven software development is closing the gap among business requirements, designs and executables by using domain-specific languages with custom-built syntax and semantics. It focuses on using modeling languages as programming languages. Among many areas of application, we highlight the area of configuration management. Consider the example of a telecommunication company, where managing the multiple configurations of network devices (routers, hubs, modems, etc.) is crucial. Enterprise systems identify and document the functional and physical characteristics of network devices, and control changes to those characteristics. Applying the integration of semantic web and model-driven software development allows for (1) explicitly specifying configurations of network devices with tailor-made languages, (2) for checking the consistency of these specifications (3) for defining a vocabulary to share device specifications across enterprise systems. By managing configurations with consistent and explicit concepts, we reduce cost and risk, and enhance agility in response to new requirements in the telecommunication area. This book examines the synergy between semantic web and model-driven software development. It brings together advances from disciplines like ontologies, description logics, domain-specific modeling, model transformation and ontology engineering to take enterprise computing to the next level.

This book is about a significant step forward in software development. It brings state-of-the-art ontology reasoning into mainstream software development and its languages. Ontology Driven Software Development is the essential, comprehensive resource on enabling technologies, consistency checking and process guidance for ontology-driven software development (ODSD). It demonstrates how to apply ontology reasoning in the lifecycle of software development, using current and emerging standards and technologies. You will learn new methodologies and infrastructures, additionally illustrated using detailed industrial case studies. The book will help you: Learn how ontology reasoning allows validations of structure models and key tasks in behavior models. Understand how to develop ODSD guidance engines for important software development activities, such as requirement engineering, domain modeling and process refinement. Become familiar with semantic standards, such as the Web Ontology Language (OWL) and the SPARQL query language. Make use of ontology reasoning, querying and justification techniques to integrate software models and to offer guidance and traceability supports. This book is helpful for undergraduate students and professionals who are interested in studying how ontologies and related semantic reasoning can be applied to the software development process. In addition, itwill also be useful for postgraduate students, professionals and researchers who are going to embark on their research in areas related to ontology or software engineering.

As the first volume of World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence, this volume is designed to lay the foundation for the understanding of the Semantic Computing (SC), as a core concept to study Robotic Intelligence in the subsequent volumes. This volume aims to provide a reference to the development of Semantic Computing, in the terms of "meaning", "context", and "intention". It brings together a series of technical notes, in average, no longer than 10 pages in length, each focuses on one topic in Semantic Computing; being review article or research paper, to explain the fundamental concepts, models or algorithms, and possible applications of the technology concerned. This volume will address three core areas in Semantic Computing: Understanding the (possibly naturally-expressed) intentions (semantics) of users and expressing them in a machine-processable format: Semantics description languages, ontology integration, interoperabilityUnderstanding the meanings (semantics) of computational content (of various sorts, including, but is not limited to, text, video, audio, process, network, software and hardware) and expressing them in a machine-processable format in Multimedia, IoT, SDN, wearable computing, interfacable with mobile computing, search engines, question answering, web services, to support applications in biomedicine, healthcare, manufacturing, engineering, education, finance, entertainment, business, science and humanityMapping the semantics of the user in context for content retrieval, management, creation in the form of structured data, image and video, audio and speech, big data, natural language, deep learning.

Introduction. Analysis techniques. Specification methods. External design. Architectural design techniques: process view. Architectural design techniques: data view. Detailed design techniques. Design validation. Software development methodologies. Bibliography. Author biographies.