Abstract
Graph transformation is a mature formalism often used as a basis for model transformation tools. Although numerous graph transformation tools exist, very few explore the paradigm of reactive, event-driven programming via incremental graph transformation. As we believe reactive programming to be a promising application for graph transformation in both research and teaching, we have developed eMoflon::IBeX as a suitable environment for incremental unidirectional model transformation via graph transformation. With eMoflon::IBeX, we have realised a novel mix of complementary tool features that have proven to be useful and effective in predecessor tools. We discuss these features and present insights based on an empirical evaluation of eMoflon::IBeX.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
The Meta Object Facility.
- 3.
Java Metadata Interface.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
With Dropbox Paper (https://www.dropbox.com/en_GB/paper), readers can communicate with authors via questions-and-answer threads directly integrated in the web-based document.
- 11.
References
Anjorin, A., Lauder, M., Patzina, S., Schürr, A.: eMoflon: leveraging EMF and professional CASE tools. In: Informatik 2011, p. 281 (2011)
Anjorin, A., Leblebici, E., Schürr, A.: 20 years of triple graph grammars: a roadmap for future research. ECEASST 73 (2015)
Anjorin, A., Robrecht, P.: Unidirectional model transformation with eMoflon::IBeX (2018). https://bit.ly/2Hw1zDa
Bergmann, G., Ráth, I., Varró, G., Varró, D.: Change-driven model transformations. SoSyM 11(3), 431–461 (2012)
Beyhl, T., Giese, H.: Incremental view maintenance for deductive graph databases using generalized discrimination networks. In: Heußner, A., Kissinger, A., Wijs, A. (eds.) GaM@ETAPS 2016. EPTCS, vol. 231, pp. 57–71 (2016)
Biermann, E., Ermel, C., Taentzer, G.: Formal foundation of consistent EMF model transformations by algebraic graph transformation. SoSyM 11(2), 227–250 (2012)
Fritsche, L., Kosiol, J., Schürr, A., Taentzer, G.: Efficient model synchronization by automatically constructed repair processes. In: Hähnle, R., van der Aalst, W. (eds.) FASE 2019. LNCS, vol. 11424, pp. 116–133. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-16722-6_7
Klar, F., Königs, A., Schürr, A.: Model transformation in the large. In: ESEC-FSE 2007, pp. 285–294. ACM, New York (2007)
Klassen, L., Wagner, R.: EMorF - a tool for model transformations. ECEASST 54 (2012)
Kluge, R., Stein, M., Giessing, D., Schürr, A., Mühlhäuser, M.: cMoflon: model-driven generation of embedded C code for wireless sensor networks. In: Anjorin, A., Espinoza, H. (eds.) ECMFA 2017. LNCS, vol. 10376, pp. 109–125. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61482-3_7
Leblebici, E., Anjorin, A., Fritsche, L., Varró, G., Schürr, A.: Leveraging incremental pattern matching techniques for model synchronisation. In: de Lara, J., Plump, D. (eds.) ICGT 2017. LNCS, vol. 10373, pp. 179–195. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61470-0_11
Leblebici, E., Anjorin, A., Schürr, A.: Developing eMoflon with eMoflon. In: Di Ruscio, D., Varró, D. (eds.) ICMT 2014. LNCS, vol. 8568, pp. 138–145. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-08789-4_10
Perez, S.M., Tisi, M., Douence, R.: Reactive model transformation with ATL. Sci. Comput. Program. 136, 1–16 (2017)
Schneider, S., Lambers, L., Orejas, F.: A logic-based incremental approach to graph repair. In: Hähnle, R., van der Aalst, W. (eds.) FASE 2019. LNCS, vol. 11424, pp. 151–167. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-16722-6_9
Varró, D., Bergmann, G., Hegedüs, Á., Horváth, Á., Ráth, I., Ujhelyi, Z.: Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework. SoSyM 15(3), 609–629 (2016)
Varró, G., Anjorin, A., Schürr, A.: Unification of compiled and interpreter-based pattern matching techniques. In: Vallecillo, A., Tolvanen, J.-P., Kindler, E., Störrle, H., Kolovos, D. (eds.) ECMFA 2012. LNCS, vol. 7349, pp. 368–383. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31491-9_28
Varró, G., Deckwerth, F.: A rete network construction algorithm for incremental pattern matching. In: Duddy, K., Kappel, G. (eds.) ICMT 2013. LNCS, vol. 7909, pp. 125–140. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38883-5_13
Weber, J.H.: GRAPE – a graph rewriting and persistence engine. In: de Lara, J., Plump, D. (eds.) ICGT 2017. LNCS, vol. 10373, pp. 209–220. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61470-0_13
Yigitbas, E., Anjorin, A., Leblebici, E., Grieger, M.: Bidirectional method patterns for language editor migration. In: Pierantonio, A., Trujillo, S. (eds.) ECMFA 2018. LNCS, vol. 10890, pp. 97–114. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92997-2_7
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Weidmann, N., Anjorin, A., Robrecht, P., Varró, G. (2019). Incremental (Unidirectional) Model Transformation with eMoflon::IBeX. In: Guerra, E., Orejas, F. (eds) Graph Transformation. ICGT 2019. Lecture Notes in Computer Science(), vol 11629. Springer, Cham. https://doi.org/10.1007/978-3-030-23611-3_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-23611-3_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23610-6
Online ISBN: 978-3-030-23611-3
eBook Packages: Computer ScienceComputer Science (R0)