Execution-Based Model Profiling

  • Alexandra Mazak
  • Manuel Wimmer
  • Polina Patsuk-Bösch
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 307)

Abstract

In model-driven engineering (MDE), models are mostly used in prescriptive ways for system engineering. While prescriptive models are indeed an important ingredient to realize a system, for later phases in the systems’ lifecycles additional model types are beneficial to use. Unfortunately, current MDE approaches mostly neglect the information upstream in terms of descriptive models from operations to (re)design phases. To tackle this limitation, we propose execution-based model profiling as a continuous process to improve prescriptive models at design-time through runtime information. This approach incorporates knowledge in terms of model profiles from execution logs of the running system. To accomplish this, we combine techniques of process mining with runtime models of MDE. In the course of a case study, we make use of a traffic light system example to demonstrate the feasibility and benefits of the introduced execution-based model profiling approach.

Notes

Acknowledgment

The authors are affiliated with the Christian Doppler Laboratory for Model-Integrated Smart Production (CDL-MINT) at TU Wien, funded by the Austrian Federal Ministry of Science, Research, and Economy (BMWFW) and the National Foundation of Research, Technology and Development (CDG). Furthermore, the authors would thank LieberLieber Software GmbH for the provisioning of the traffic light example.

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Alexandra Mazak
    • 1
  • Manuel Wimmer
    • 1
  • Polina Patsuk-Bösch
    • 1
  1. 1.Christian Doppler Laboratory for Model-Integrated Smart Production (CDL-MINT), Institute of Software Technology and Interactive SystemsTU WienViennaAustria

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