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On the Need for Data-Based Model-Driven Engineering

  • Alexandra MazakEmail author
  • Sabine Wolny
  • Manuel Wimmer
Chapter

Abstract

In order to deal with the increasing complexity of modern systems such as in software-intensive environments, models are used in many research fields as abstract descriptions of reality. On the one side, a model serves as an abstraction for a specific purpose, as a kind of “blueprint” of a system, describing a system’s structure and desired behavior in the design phase. On the other side, there are so-called runtime models providing real abstractions of systems during runtime, for example, to monitor runtime behavior. Today, we recognize a discrepancy between the early snapshots and their real-world correspondents. To overcome this discrepancy, we propose to fully integrate models from the very beginning within the life cycle of a system. As a first step in this direction, we introduce a data-based model-driven engineering approach where we provide a unifying framework to combine downstream information from the model-driven engineering process with upstream information gathered during a system’s operation at runtime, by explicitly considering also a timing component. We present this temporal model framework step-by-step by selected use cases with increasing complexity.

Keywords

Model-driven engineering Data-driven engineering Model repositories Model profiling Sequence mining 

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Notes

Acknowledgements

This work has been supported by the Austrian Federal Ministry for Digital and Economic Affairs; by the National Foundation for Research, Technology and Development; and by the FWF in the Project TETRABox under the grant number P28519-N31.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Christian Doppler Laboratory for Model-Integrated Smart Production (CDL-MINT)WIN-SE, JKU LinzLinzAustria

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