volume 20 issue 4 pages 597-618

Empowering model repair: a rule-based approach to graph repair without side effects—extended version

Publication typeJournal Article
Publication date2024-11-04
scimago Q3
wos Q4
SJR0.371
CiteScore4.7
Impact factor1.1
ISSN16145046, 16145054
Abstract

Working with models can lead to inconsistencies, e.g., due to erroneous or contradictory actions during concurrent modeling processes. Modern modeling environments typically tolerate inconsistencies and support their detection. However, at a later stage of development, models are expected to be consistent, meaning their inconsistencies should be considered and resolved. The process of resolving model inconsistencies is commonly referred to as model repair. Our approach to model repair is semi-automatic in the sense that the repair tool computes appropriate repair plans and the modeler decides which path to take. The speciality of our approach is that the repair process can register any small improvement in the model. This allows the interaction with the user to be optimized, resulting in an approach with a high level of automation on the one hand and flexible configuration options on the other. The approach focuses on providing repair plans that do not have side effects, i.e., the computed repair plans do not inadvertently introduce a new inconsistency of already repaired constraints into the model. Since models often have a graph-like structure, we present our approach to model repair based on graphs. Our approach is completely formal—we use the algebraic graph transformation approach to prove its correctness. We also present a prototype implementation of our repair approach based on the Eclipse Modeling Framework and Henshin, a model transformation engine based on graph transformation, to perform the actual model repair. A first performance evaluation shows that graphs with up to 1000 nodes can be repaired in about 10 s.

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Lauer A. et al. Empowering model repair: a rule-based approach to graph repair without side effects—extended version // Innovations in Systems and Software Engineering. 2024. Vol. 20. No. 4. pp. 597-618.
GOST all authors (up to 50) Copy
Lauer A., Kosiol J., Taentzer G. Empowering model repair: a rule-based approach to graph repair without side effects—extended version // Innovations in Systems and Software Engineering. 2024. Vol. 20. No. 4. pp. 597-618.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1007/s11334-024-00587-w
UR - https://link.springer.com/10.1007/s11334-024-00587-w
TI - Empowering model repair: a rule-based approach to graph repair without side effects—extended version
T2 - Innovations in Systems and Software Engineering
AU - Lauer, Alexander
AU - Kosiol, Jens
AU - Taentzer, Gabriele
PY - 2024
DA - 2024/11/04
PB - Springer Nature
SP - 597-618
IS - 4
VL - 20
SN - 1614-5046
SN - 1614-5054
ER -
BibTex |
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BibTex (up to 50 authors) Copy
@article{2024_Lauer,
author = {Alexander Lauer and Jens Kosiol and Gabriele Taentzer},
title = {Empowering model repair: a rule-based approach to graph repair without side effects—extended version},
journal = {Innovations in Systems and Software Engineering},
year = {2024},
volume = {20},
publisher = {Springer Nature},
month = {nov},
url = {https://link.springer.com/10.1007/s11334-024-00587-w},
number = {4},
pages = {597--618},
doi = {10.1007/s11334-024-00587-w}
}
MLA
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MLA Copy
Lauer, Alexander, et al. “Empowering model repair: a rule-based approach to graph repair without side effects—extended version.” Innovations in Systems and Software Engineering, vol. 20, no. 4, Nov. 2024, pp. 597-618. https://link.springer.com/10.1007/s11334-024-00587-w.