Abstract
Metamodels are a central artifact of model-driven engineering. As they determine the structure of instance models, they are a foundation for other model-driven artifacts such as model transformations, code generators or model analyses. Therefore, the quality of metamodels is important for any model-driven process. However, the implications of metamodel design to other artifacts such as model analyses or model transformations has barely been looked at through empirical research. In this paper, we present an empirical study where we analyzed equivalent model analyses and transformations for 19 different metamodels of the same domain. The results indicate that metamodel design has a strong influence to model analysis in terms of code metrics but only little influence on model transformations targeting this metamodel.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
- 2.
In [10], we also introduced an adapted version of module uniformity (MU) but we discarded this metric as it showed major weaknesses.
- 3.
In contrast to [16], Visual Studio rescales the maintainability index to fit into the value range of 0 to 100.
- 4.
- 5.
The metric set by van Amstel does not include a metric to measure the complexity of model transformation rules, so we might have seen results if we had a proper metric.
- 6.
See [20] for a usage example.
References
Hinkel, G., Groenda, H., Vannucci, L., Denninger, O., Cauli, N., Ulbrich, S.: A domain-specific language (DSL) for integrating neuronal networks in robot control. In: 2015 Joint MORSE/VAO Workshop on Model-Driven Robot Software Engineering and View-Based Software-Engineering (2015)
Hinkel, G., Groenda, H., Krach, S., Vannucci, L., Denninger, O., Cauli, N., Ulbrich, S., Roennau, A., Falotico, E., Gewaltig, M.-O., Knoll, A., Dillmann, R., Laschi, C., Reussner, R.: A framework for coupled simulations of robots and spiking neuronal networks. J. Intell. Robot. Syst. 85, 71–91 (2016)
Lehman, M.M.: Programs, cities, students: limits to growth? (Inaugural Lecture - Imperial College of Science and Technology, 1974). University of London, Imperial College of Science and Technology (1974)
Lehman, M., Ramil, J., Wernick, P., Perry, D., Turski, W.: Metrics and laws of software evolution-the nineties view. In: Proceedings of the Fourth International Software Metrics Symposium, pp. 20–32 (1997)
Schmidt, D.C.: Model-driven engineering. IEEE Comput. 39(2), 25 (2006)
Di Ruscio, D., Iovino, L., Pierantonio, A.: Evolutionary togetherness: how to manage coupled evolution in metamodeling ecosystems. In: Ehrig, H., Engels, G., Kreowski, H.-J., Rozenberg, G. (eds.) ICGT 2012. LNCS, vol. 7562, pp. 20–37. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33654-6_2
Di Rocco, J., Di Ruscio, D., Iovino, L., Pierantonio, A.: Mining correlations of ATL model transformation and metamodel metrics. In: Proceedings of the Seventh International Workshop on Modeling in Software Engineering, pp. 54–59. IEEE Press (2015)
Di Rocco, J., Di Ruscio, D., Iovino, L., Pierantonio, A.: Mining metrics for understanding metamodel characteristics. In: Proceedings of the 6th International Workshop on Modeling in Software Engineering, MiSE 2014, pp. 55–60. ACM (2014)
Hinkel, G., Kramer, M., Burger, E., Strittmatter, M., Happe, L.: An empirical study on the perception of metamodel quality. In: Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development, pp. 145–152 (2016)
Hinkel, G., Strittmatter, M.: On using Sarkar metrics to evaluate the modularity of metamodels. In: Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development (2017)
Reussner, R.H., Becker, S., Happe, J., Heinrich, R., Koziolek, A., Koziolek, H., Kramer, M., Krogmann, K.: Modeling and Simulating Software Architectures - The Palladio Approach. MIT Press, Cambridge (2016). 408 pp.
Hinkel, G.: NMF: a modeling framework for the .NET platform. Technical report, Karlsruhe Institute of Technology (2016)
Akehurst, D.H., Howells, W.G.J., Scheidgen, M., McDonald- Maier, K.D.: C# 3.0 makes OCL redundant. In: Electronic Communications of the EASST, vol. 9 (2008)
Jouault, F., Kurtev, I.: Transforming models with ATL. In: Bruel, J.-M. (ed.) MODELS 2005. LNCS, vol. 3844, pp. 128–138. Springer, Heidelberg (2006). https://doi.org/10.1007/11663430_14
Troya, J., Vallecillo, A.: A rewriting logic semantics for ATL. J. Object Technol. 10(5), 1–29 (2011)
Oman, P., Hagemeister, J.: Metrics for assessing a software system’s maintainability. In: Proceedings of the Conference on Software Maintenance, pp. 337–344. IEEE (1992)
van Amstel, M., van den Brand, M.: Using metrics for assessing the quality of ATL model transformations. In: Proceedings of the Third International Workshop on Model Transformation with ATL (MtATL 2011), vol. 742, pp. 20–34 (2011)
Zhou, Y., Leung, H.: Empirical analysis of object-oriented design metrics for predicting high and low severity faults. IEEE Trans. Softw. Eng. 32(10), 771–789 (2006)
Hinkel, G., Strittmatter, M.: Predicting the perceived modularity of MOF-based metamodels. In: Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development (2018)
Hinkel, G., Happe, L.: An NMF solution to the TTC train benchmark case. In: Proceedings of the 8th Transformation Tool Contest, a Part of the Software Technologies: Applications and Foundations (STAF 2015) Federation of Conferences, CEUR Workshop Proceedings, vol. 1524, pp. 142–146. CEURWS.org (2015)
Hinkel, G., Burger, E.: Change propagation and bidirectionality in internal transformation DSLs. Softw. Syst. Model. (2017)
Acknowledgements
We would like to thank all students that participated in our study as well as Frederik Petersen and Lennart Henseler who helped us creating the model transformations and analyses.
This research has received funding from the European Union Horizon 2020 Future and Emerging Technologies Programme (H2020-EU.1.2.FET) under grant agreement no. 720270 (Human Brain Project SGA-I).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Hinkel, G., Burger, E. (2018). On the Influence of Metamodel Design to Analyses and Transformations. In: Pierantonio, A., Trujillo, S. (eds) Modelling Foundations and Applications. ECMFA 2018. Lecture Notes in Computer Science(), vol 10890. Springer, Cham. https://doi.org/10.1007/978-3-319-92997-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-92997-2_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92996-5
Online ISBN: 978-3-319-92997-2
eBook Packages: Computer ScienceComputer Science (R0)