A practical approach to enhancing quality in software models using UML Version 2.0 "Despite its increasing usage, many companies are not taking the best advantage of UML and, occasionally, individuals have experienced frustration in applying its standards. Perhaps this is because they have not yet read this book!" -From the Foreword by Prof. Brian Henderson-Sellers This book presents a practical checklist approach to enhancing the quality of software models created with the Unified Modeling Language (UML) Version 2.0. The foundation for quality is set by the discussion on the nature and creation of UML models. This is followed by a demonstration of how to apply verification and validation checks to these models with three foci: syntactical correctness, semantic meaningfulness, and aesthetic symmetry. The quality work is carried out within three distinct yet related modeling spaces: * Model of problem space (MOPS) * Model of solution space (MOSS) * Model of background space (MOBS) Readers can then choose a specific quality approach according to their roles in their projects. Verification and validation checks are also organized according to these three modeling spaces, making it easier for the reader to focus on the appropriate diagrams and quality checks corresponding to their modeling space. In addition, a major element of this publication is the Strengths, Weaknesses, Objectives, and Traps (SWOT) analysis. This analysis is performed on each UML diagram, enabling readers to fully comprehend these diagrams, their advantages and limitations, and the way in which they can be used in practical projects for modeling. A consistent case study of the Lucky Insurance System is provided throughout the chapters to illustrate the creation of good quality UML diagrams, followed by application of quality checks to them. With its emphasis on quality in UML-based projects, this book is an essential resource for all quality professionals, including quality analysts, process consultants, quality managers, test designers, and testers.

This book covers state-of-the art techniques for high-level modeling and validation of complex hardware/software systems, including those with multicore architectures. Readers will learn to avoid time-consuming and error-prone validation from the comprehensive coverage of system-level validation, including high-level modeling of designs and faults, automated generation of directed tests, and efficient validation methodology using directed tests and assertions. The methodologies described in this book will help designers to improve the quality of their validation, performing as much validation as possible in the early stages of the design, while reducing the overall validation effort and cost.

This book constitutes the refereed joint proceedings of six workshops held in conjunction with the 26th International Conference on Conceptual Modeling. Topics include conceptual modeling for life sciences applications, foundations and practices of UML, ontologies and information systems for the semantic Web , quality of information systems, requirements, intentions and goals in conceptual modeling, and semantic and conceptual issues in geographic information systems.

Models are used in all kinds of engineering disciplines to abstract from the various details of the modelled entity in order to focus on a speci?c aspect. Like a blueprint in civil engineering, a software architecture providesan abstraction from the full software system’s complexity. It allows software designers to get an overview on the system underdevelopmentandtoanalyzeitsproperties.Inthissense,modelsarethefoundation needed for software development to become a true engineering discipline. Especially when reasoning on a software system’s extra-functional properties, its software architecture carries the necessary information for early, design-time analyses. These analyses take the software architecture as input and can be used to direct the design process by allowing a systematic evaluation of different design alternatives. For example, they can be used to cancel out decisions which would lead to architecture - signs whose implementation would not comply with extra-functionalrequirements like performance or reliability constraints. Besides such quality attributes directly visible to the end user, internal quality attributes, e.g., maintainability, also highly depend on the system’s architecture. In addition to the above-mentioned technical aspects of software architecture m- els, non-technical aspects, especially project management-related activities, require an explicit software architecture model. The models are used as input for cost esti- tions, time-, deadline-, and resource planning for the development teams. They serve the project management activities of planning, executing, and controlling, which are necessary to deliver high-quality software systems in time and within the budget.

This book constitutes the refereed proceedings of the Third European Conference on Model Driven Architecture: Foundations and Applications, ECMDA-FA 2007, held in Haifa, Israel in June 2007. The papers address all current issues of model-driven architecture, including foundational topics and application–oriented issues.

With its clear introduction to the Unified Modeling Language (UML) 2.0, this tutorial offers a solid understanding of each topic, covering foundational concepts of object-orientation and an introduction to each of the UML diagram types.

New techniques and tools for database and database technologies are continuously being introduced. These technologies are the heart of many business information systems and can benefit from theories, models, and research results from other disciplines. Innovations in Database Design, Web Applications, and Information Systems Management presents ideal research in the areas of database theory, systems design, ontologies, and many more. Including examples of the convergence of ideas from various disciplines aimed at improving and developing the theory of information technology and management of information resources, this book is useful for researchers and practitioners in the IT field.