Model Management and Analytics for Large Scale Systems [Pehme köide]

Edited by , Edited by (Full Professor, Information Technology Group, Wageningen University, The Netherlands), Edited by (Assistant Professor, Departmen), Edited by (Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands), Edited by
  • Formaat: Paperback / softback, 344 pages, kõrgus x laius: 235x191 mm, kaal: 720 g
  • Ilmumisaeg: 17-Sep-2019
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128166495
  • ISBN-13: 9780128166499
  • Formaat: Paperback / softback, 344 pages, kõrgus x laius: 235x191 mm, kaal: 720 g
  • Ilmumisaeg: 17-Sep-2019
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128166495
  • ISBN-13: 9780128166499

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics.

This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.

  • Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics
  • Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics
  • Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
1. Concepts and challenges
1. Introduction to modelmanagement and analytics
2. Challenges and directions for a community infrastructure for Big Data-driven research in software architecture
3. Model clone detection and its role in emergent model pattern mining
4. Domain-driven analysis of architecture reconstruction methods Part
2. Methods and tools
5. Monitoring model analytics over large repositories with Hawk and MEASURE
6. Model analytics for defect prediction based on design-level metrics and sampling techniques
7. Structuring large models with MONO: Notations, templates, and case studies
8. Delta-oriented development of model-based software product lines with DeltaEcore and SiPL: A comparison
9. OptML framework and its application tomodel optimization Part
3. Industrial applications
10. Reducing design time and promoting evolvability using Domain-Specific Languages in an industrial context
11. Model analytics for industrialMDE ecosystems
Bedir Tekinerdogan is a full professor and chair of the Information Technology group at Wageningen University in The Netherlands. He received his MSc degree (1994) and a PhD degree (2000) in Computer Science, both from the University of Twente, The Netherlands. From 2003 until 2008 he was a faculty member at University of Twente, after which he joined Bilkent University until 2015. He has more than 20 years of experience in software engineering research and education. His main research includes the engineering of smart software-intensive systems. In particular, he has focused on and is interested in software architecture design, software product line engineering, model-driven development, parallel computing, cloud computing and system of systems engineering. He has been active in dozens of national and international research and consultancy projects with various large software companies whereby he has worked as a principal researcher and leading software/system architect. He has reviewed more than 100 national and international software research and development projects and is a regular reviewer for around 20 international journals. He graduated around 40 MSc students and supervised more than 10 PhD students. He has developed and taught more than 15 different academic software engineering courses and has provided software engineering courses to more than 50 companies in The Netherlands, Germany and Turkey. OEnder Babur is a post-doctoral researcher in the Software Engineering & Technology (SET) group at Eindhoven University of Technology. He holds a PhD from Eindhoven University of Technology, The Netherlands; MSc from RWTH Aachen, Germany and BSc from METU, Turkey. He has further experience as a software engineer in Germany and as a researcher in Spain. His main research interests lie in the fields of model-driven engineering, software architectures, domain-specific languages, and recently applied data mining and machine learning for those domains. Over the years, he has been involved in a number of research projects on automotive software engineering and software product lines, green computing and multiscale modeling for computational science. He currently focuses on data science and machine learning applications for model analytics and management, where he publishes his work in international venues and cooperates with high tech companies. Loek Cleophas is an assistant professor in the Model-Driven Software Engineering (MDSE) section at Eindhoven University of Technology (TU/e) and a research fellow at Stellenbosch University, South Africa. He obtained his doctorate in computer science and engineering at TU/e. His work in MDSE has varied from model-driven virtualization of high-tech systems, to generating efficient algorithm toolkits based on algorithm taxonomies. More recent work focuses on analyzing large collections of models and extracting variability and commonality information from them. His research in algorithm engineering and algorithm comparison focuses on pattern matching and finite automata for processing text and tree-shaped data. He worked in industry in the Netherlands and the USA, and at universities in South Africa, Sweden, and Germany, on research funded by various national and international projects as well as by industrial partners. He is also managing director of the Dutch research school on programming and algorithmics (IPA). Mark van den Brand is a Full Professor Software Engineering and Technology of the section Model Driven Software Engineering, Eindhoven University of Technology (TU/e). He got his PhD from the Radboud University (The Netherlands) in 1992. He worked as assistant professor at the University of Amsterdam after his PhD and moved in 1997 to CWI to work there as senior researcher for almost 10 years. In his Amsterdam period he worked on grammar based technologies to describe the syntax and semantics of programming languages. He was responsible for the redesign of the ASF+SDF Meta-Environment, a language workbench. Using ASF+SDF he worked on developing grammars and transformations for legacy languages. He also worked on the defining the syntax and semantics of domain specific languages. He published papers on both on the technologies developed for the ASF+SDF Meta-Environment as well as papers on applications of ASF+SDF. In this period he initiated the workshop series Language Descriptions, Tools and Applications (LDTA) that later on continued into the international conference on Software Language Engineering (SLE). He served for quite a number of years on the steering committee of SLE. Since 2006, he is a full professor of Software Engineering and Technology in the Department of Mathematics and Computer Science, and a visiting professor at Royal Holloway, University of London. His current research activities are on generic language technology, model driven engineering, domain specific models, meta-modeling, reverse engineering, and automotive software engineering. His research is industry inspired; he works with most of the high-tech companies in the Eindhoven (The Netherlands) region. He has been an invited lecturer and keynote speaker at various conferences, workshops and doctoral schools. He was and is member of PCs on workshops and conferences related to software engineering, language engineering, rewriting, reverse engineering, and software maintenance. He initiated the special issues of Science of Computer Programming devoted to academic software development (Experimental Software and Toolkits), and since 2007 has been guest editor of six of these. He is on the editorial board of the journals Science of Computer Programming and Open Computer Science. He is Editor-in-Chief of the Journal on Automotive Software Engineering. He is associate Editor-in-Chief of the Software Section of the Science of Computer Programming. He is associate Editor of the Journal of Object Technology. Mehmet Aksit holds an M.Sc. from the Eindhoven University of Technology and a Ph.D. from the University of Twente. He (and his group) have pioneered the following techniques: Programming languages: In 1988, (probably the first) aspect-oriented language called Sina was developed. This work was later evolved into the concept of Composition Filters (1992). Various languages adopted this concept (ComposeJ, Compose*, etc.). From 2010, new language abstractions (Event Composition Modules, the Gummy programming language) were developed to abstract event-based programs. A particular interest was to modularly represent so-called "emergent behaviour". Software design: In the 90's, a fuzzy-logic based technique for modelling uncertainty in software design processes was developed. Later, this technique was extended with fuzzy-probabilistic methods and applied to software process- and product-optimization problems. Product-line and/or software architectures/application frameworks: Since 1990's, various industrial projects have been carried out with companies to design and implement application specific libraries, product-line architectures, application frameworks, domain-specific languages, etc. For example, as 2018, we were told that every lithography machine produced by the company ASML (owns about 70% of the world market) has a subsystem that was originally designed and implement by our research team. Also, new design formalisms were developed to evaluate various software quality attributes. University - Industry cooperation methods: Since 2011, as a team, we have been developing new "university - industry cooperation" methods. Along this line, company maturity models and processes have been defined. This method aims at enhancing the capabilities of high-technology companies so that they can accomplish their strategic objectives in a timely manner.

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