Software & Systems Modeling

, Volume 16, Issue 2, pp 333–356 | Cite as

On the complex nature of MDE evolution and its impact on changeability

  • Regina Hebig
  • Holger Giese
Special Section Paper


In model-driven engineering (MDE), a particular MDE setting of employed languages and automated and manual activities has major impact on productivity. Furthermore, it has been observed that such MDE settings evolve over time. However, currently not much is known about this evolution and its impact on the MDE setting’s maturity, i.e., on changeability and other productivity dimensions. Research so far focuses on evolution of separate building blocks, such as (modeling-) languages, tools, or transformation, only. In this article, we address the lack of knowledge about evolution of MDE settings by investigating case studies from different companies. The first results reveal (1) that there is evolution that affects the composition of an MDE setting (structural evolution) and has the potential to strongly impact aspects, such as changeability and (2) that this structural evolution actually occurs in practice. Based on these first results, we investigated (3) whether there are cases in practice, where structural evolution already altered the risks of changeability given by the respective MDE setting. Therefore, we search and identify examples for such evolution steps on MDE settings from practice and collected six case studies on evolution histories in detail. As a result, we show in this paper that structural evolution (a) is not seldom in practice and (b) sometimes leads to the introduction of changeability risks.


Model-driven engineering Evolution Empirical research 



First of all, the authors appreciate the valuable feedback of Florian Stallmann and Andreas Seibel, who co-authored the conference paper [14]. We are also grateful to the participants of our studies with SAP, Carmeq, VCat, and Capgemini and especially Axel Uhl, Cafer Tosun, Gregor Engels, and Marion Kremer for their support in choosing the case studies and for making this research possible. We are thankful to Hannelore Liero and Hilmar Buchholz for hints and feedback on the statistical analysis. Further, we thank the HPI Research School on Service-Oriented Systems Engineering for funding parts of this research. Last but not least, we want to thank the anonymous reviewers of this article for their constructive feedback, which helped us to improve the paper.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.LIP6, UMR 7606Sorbonne Universités, UPMC Univ Paris 06ParisFrance
  2. 2.Hasso Plattner InstituteUniversity of PotsdamPotsdamGermany

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