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.
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Table of Contents
Part 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
Authors
Bedir Tekinerdogan Full Professor, Information Technology Group, Wageningen University and Research, The Netherlands. 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 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. �nder Babur Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. �nder 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 Assistant Professor, Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. 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 Full Professor, Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands. 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 Full Professor, Department of Engineering, TOBB University of Economics and Technology, Ankora, Turkey. Dr. Aksit is currently a Full Professor at TOBB ET� and the Director of the Smart-Cities and Digital Ecosystems Research Lab. He holds an M.Sc. degree from the Eindhoven University of Technology and a Ph.D. degree from the University of Twente. He was Full Professor and Software Engineering Chair at the University of Twente (2000-2019). As a visiting scientist, in 1989 he was at the IBM T. J. Watson Research Laboratory, New York, in 1993 at the University of Tokyo, in 1994 at the New Jersey Institute of Technology and in 2019 at University of Malaya at KL. He and the members of the group were the pioneers of aspect-oriented programming (Sina & Composition Filters), synthesis based controlled problem-solving techniques, fuzzy-logic based techniques to modelling software design heuristics and processes, software architecture design methods and software metrics. He has given courses in Canada, Denmark, France, Germany, Hungary, Ireland, Italy, Netherlands, Portugal, Spain, Sweden, Switzerland, Turkey and in the US. He has organized special training programs for multi-national companies. He has designed various large-scale software architectures, which some of them are currently being utilized in products. Some of the research tools developed by the chair are now being used in some industrial applications.He has been working as a consultant for Dutch Ministry of Traffic, Dutch Tax office, Ericsson, Philips, ASML, Oc�, Thales, Beko-Grundig, TAI, Aselsan, Havelsan, Roketsan, Capgemini, Siemens, Softtech. He has served in the review and strategic planning for various EU projects.
With the T�BITAK grant, " Outstanding International Researchers", he has established the Smart-City Research Lab in Ankara. As an application of smart-City systems, he has recently focused on managing pandemic disasters. To this aim, he has pioneered the establishment of the Alliance on Digital Management of Pandemic Disasters.
