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 involded 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 :

    • 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, School of Computer Science,Reykjavik University
    • 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, FCT/UNL, Portugal
    • Timo Kehrer, Humboldt-Universität zu Berlin, Germany
    • Daniel Strüber, Chalmers University of Technology and University of Gothenburg, Sweden

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.