An Extensible Component Connector Architecture Description Infrastructure For Multi Platform Modeling

Software engineering for complex systems requires abstraction, multi-domain expertise, separation of concerns, and reuse. Domain experts rarely are software engineers and should formulate solutions using their domain's vocabulary instead of general purpose programming languages (GPLs). Successful integration of domain-specific languages (DSLs) into a software system requires a separation of concerns between domain issues and integration issues while retaining a loose enough coupling to support DSL reuse in different contexts. Component-based software engineering (CBSE) increases reuse and separation of concerns by encapsulating functionalities in components. Components are GPL artifacts, which raises accidental complexities. Model-driven engineering (MDE) abstracts from GPLs by lifting models to primary development artifacts. Models can be abstract and better comprehensible by using domain vocabulary instead of a GPL. They can be platform-independent and translated into GPLs for different target platforms. Component & connector (C&C) architecture description languages (ADLs) combine CBSE and MDE to compose of architectures from component models. We present concepts for engineering software systems with exchangeable component behavior languages. The concepts are realized in a software architecture modeling infrastructure that comprises modeling languages to develop applications based on C&C software architectures with exchangeable component behavior DSLs. It supports transformations from platform-independent to platform-specific software architectures and compositional code generation. With this, it enables domain experts to (re-)use the most appropriate component behavior DSL and facilitates composition of domain solutions through encapsulation in components.

Software has become ever more crucial as an enabler, from daily routines to important national decisions. But from time to time, as society adapts to frequent and rapid changes in technology, software development fails to come up to expectations due to issues with efficiency, reliability and security, and with the robustness of methodologies, tools and techniques not keeping pace with the rapidly evolving market. This book presents the proceedings of SoMeT_19, the 18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, held in Kuching, Malaysia, from 23–25 September 2019. The book explores new trends and theories that highlight the direction and development of software methodologies, tools and techniques, and aims to capture the essence of a new state of the art in software science and its supporting technology, and to identify the challenges that such a technology will have to master. The book also investigates other comparable theories and practices in software science, including emerging technologies, from their computational foundations in terms of models, methodologies, and tools. The 56 papers included here are divided into 5 chapters: Intelligent software systems design and techniques in software engineering; Machine learning techniques for software systems; Requirements engineering, software design and development techniques; Software methodologies, tools and techniques for industry; and Knowledge science and intelligent computing. This comprehensive overview of information systems and research projects will be invaluable to all those whose work involves the assessment and solution of real-world software problems.

Provides modern enterprises with the tools to create a robust digital platform utilizing proven best practices, practical models, and time-tested techniques Contemporary business organizations can either embrace the digital revolution—or be left behind. Enterprise Content and Search Management for Building Digital Platforms provides modern enterprises with the necessary tools to create a robust digital platform utilizing proven best practices, practical models, and time-tested techniques to compete in the today’s digital world. Features include comprehensive discussions on content strategy, content key performance indicators (KPIs), mobile-first strategy, content assessment models, various practical techniques and methodologies successfully used in real-world digital programs, relevant case studies, and more. Initial chapters cover core concepts of a content management system (CMS), including content strategy; CMS architecture, templates, and workflow; reference architectures, information architecture, taxonomy, and content metadata. Advanced CMS topics are then covered, with chapters on integration, content standards, digital asset management (DAM), document management, and content migration, evaluation, validation, maintenance, analytics, SEO, security, infrastructure, and performance. The basics of enterprise search technologies are explored next, and address enterprise search architecture, advanced search, operations, and governance. Final chapters then focus on enterprise program management and feature coverage of various concepts of digital program management and best practices—along with an illuminating end-to-end digital program case study. Offers a comprehensive guide to the understanding and learning of new methodologies, techniques, and models for the creation of an end-to-end digital system Addresses a wide variety of proven best practices and deployed techniques in content management and enterprise search space which can be readily used for digital programs Covers the latest digital trends such as mobile-first strategy, responsive design, adaptive content design, micro services architecture, semantic search and such and also utilizes sample reference architecture for implementing solutions Features numerous case studies to enhance comprehension, including a complete end-to-end digital program case study Provides readily usable content management checklists and templates for defining content strategy, CMS evaluation, search evaluation and DAM evaluation Comprehensive and cutting-edge, Enterprise Content and Search Management for Building Digital Platforms is an invaluable reference resource for creating an optimal enterprise digital eco-system to meet the challenges of today’s hyper-connected world.

Take Part in the Future of Wireless/Wireline Convergence The IP multimedia subsystem (IMS), established as the foundation for future wireless and wireline convergence, is the bedrock that will facilitate easy deployment on new, rich, personalized multimedia communication services that mix telecom and data services. Designers, planners, and researchers of communication systems will need to make full use of the technology occurring with this convergence if they want to be the ones providing end users with new and efficient services that are as cost-effective as they are innovative. To provide researchers and technicians with the tools they need to optimize their role in this communication revolution, the IP Multimedia Subsystem (IMS) Handbook presents all the technical aspects of the IMS needed to support the growth of digital traffic and the implementation of underlying networks. This guide covers everything from basic concepts to research-grade material, including the future direction of the architecture. Organized in three sections, the book brings together the technical savvy of 50 pioneering experts from around the world, providing complete coverage of relevant concepts, technologies, and services. Learn How IMS Will Speed Innovation Filling the gap between existing traditional telecommunications and Internet technologies, IMS has led to an environment in which new services and concepts are introduced more quickly than ever before, such as reusable service components and real-time integration. The technology promises to be a cost-effective evolutionary path to future wireless and wireline convergences that will meet next-generation service requirements.

Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.

This book provides a unique overview of different approaches to developing software that is flexible, adaptable and easy to maintain and reuse. It covers the most recent advances in software architecture research. In addition, it provides the reader with scalable solutions for engineering and reengineering business processes, including architectural components for business applications, framework design for Internet distributed business applications, and architectural standards for enterprise systems.

The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.