Abstract
This paper proposes and evaluates an efficient approach for loading models stored in a change-based format. The work builds on language-independent change-based persistence (CBP) of models conforming to object-oriented metamodelling architectures such as MOF and EMF, an approach which persists a model’s editing history rather than its current state. We evaluate the performance of the proposed loading approach and assess its impact on saving change-based models. Our results show that the proposed approach significantly improves loading times compared to the baseline CBP loading approach, and has a negligible impact on saving.
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Notes
- 1.
The commented parts show the end states of children after each event.
- 2.
The prototype, tests, and data used in the evaluation are available under https://github.com/epsilonlabs/emf-cbp and https://goo.gl/1zUBQC for reproducibility.
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Acknowledgements
This work was partly supported by through a scholarship managed by Lembaga Pengelola Dana Pendidikan Indonesia (Indonesia Endowment Fund for Education).
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Yohannis, A., Rodriguez, H.H., Polack, F., Kolovos, D. (2018). Towards Efficient Loading of Change-Based Models. 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_15
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