Track: Model-Driven Methods
ABOUT
Model-driven engineering (MDE) refers to a broad range of approaches where models play an indispensable role in software development. Modeling promotes higher level of abstraction, therefore reducing complexity of software development and promoting communication among the several stakeholders involved in the lifecycle of software systems (e.g., product managers, analysts, designers, programmers, operators to name just a few). MDE initiatives, such as Domain-Specific Modeling (DSM), make claims of increased quality and productivity by separating business and application logic from underlying platform technology, transforming models to other models (e.g., for validation and verification) and automating code generation (ranging from system skeletons to complete, deployable products). However, while quality assurance is a well-known topic in “traditional” Software Engineering, less is known on how to assess quality across the MDE lifecycle (encompassing new activities such as metamodel-based language engineering or transformation engineering such as template-based code generation), as well as on the effective improvements obtained by applying MDE itself including the quality of the MDE technologies.
We seek novel contributions ranging from conceptual frameworks over tool supported methodologies to case studies and experiments on how to leverage ICT systems quality with MDE techniques, as well as how to induce quality assurance in the MDE lifecycle itself.
TOPICS
The suggested topics of interest include, but are not restricted to:
Quality models in the MDE context
Quality assurance in the MDE development flow
Evaluating the quality of models, metamodels, and transformations
Models’ traceability throughout the complete lifecycle including operations
Measuring the improvement achieved with an MDE approach, specially regarding quality
Quality in the context of model-driven service oriented systems
Case studies and lessons learned in applying MDE in industry
Empirical studies on the quality of MDE processes
Studying the quality of MDE technologies
Modeling and analyzing quality standards
Role of MDE in the quality evaluation of software maintenance, evolution and migration scenarios
TRACK COMMITTEE
Track Chair: Manuel Wimmer, Johannes Kepler University Linz, Austria
Program Committee :
Loli Burgueño, Open University of Catalonia & CEA LIST, Spain
Andreas Wortmann, RWTH Aachen, Germany
Antonio Cicchetti, Mälardalen University, Sweden
Antonio Vallecillo, Universidad de Malaga, Spain
Benoit Combemale, University of Toulouse, France
Eugene Syriani, University of Montreal, Canada
Geylani Kardas, Ege University, Turkey
Grischa Liebel, Reykjavik University, Iceland
Gustavo Rossi, Universidad Nacional de La Plata, Argentina
Ivano Malavolta, Vrije Universiteit Amsterdam, the Netherlands
Javier Troya, Universidad de Sevilla, Spain
Juan de Lara, Universidad Autónoma de Madrid, Spain
Juan Manuel Vara Mesa, Rey Juan Carlos University, Spain
Ludovico Iovino, Gran Sasso Science Institute, Italy
Marcos Didonet Del Fabro, Universidade Federal do Paraná, Brazil
Robert Clarisó, Universitat Oberta de Catalunya, Spain
Valter V. Camargo, Federal University of São Carlos, Brazil
Vasco Amaral, Universidade NOVA de Lisboa, Portugal
Timo Kehrer, Humboldt-Universität zu Berlin, Germany
Daniel Strüber, Radboud University Nijmegen, the Netherlands
Stefan Klikovits, National Institute of Informatics, Japan
Alberto Silva, Universidade de Lisboa, Portugal
Manuel Wimmer is Full Professor and Head of the Department of Business Informatics – Software Engineering at JKU Linz, Austria. He received his Ph.D. and his Habilitation from TU Wien. He has been a research associate at the University of Malaga, Spain, a visiting professor at the University of Marburg, Germany as well as at TU Munich, Germany, and an assistant professor at the Business Informatics Group (BIG), TU Wien, Austria.
Currently, he is leading the Christian Doppler Laboratoy on Model-Integrated Smart Production (CDL-MINT) which is running from 2017 to 2023. In this context, he is developing modeling approaches for smart production facilities, as well as techniques for the continuous evolution of such systems based on production information gathered and analyzed at runtime. In this context, he is also the JKU Linz representative within the AutomationML society. He is coauthor of the book Model-driven Software Engineering in Practice (Morgan & Claypool, 2nd edition, 2017).
For a list of scientific publications see the entries in DBLP and Google Scholar.
PREVIOUS TRACK EDITIONS
QUATIC 2019, QUATIC 2018, QUATIC 2016, QUATIC 2014, QUATIC 2012, QUATIC 2010