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Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Fritsche, Lars ; Kosiol, Jens ; Schürr, Andy ; Taentzer, Gabriele (2024)
Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars.
In: International Journal on Software Tools for Technology Transfer, 2021, 23 (3)
doi: 10.26083/tuprints-00023912
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars
Language: English
Date: 30 April 2024
Place of Publication: Darmstadt
Year of primary publication: June 2021
Place of primary publication: Berlin ; Heidelberg
Publisher: Springer
Journal or Publication Title: International Journal on Software Tools for Technology Transfer
Volume of the journal: 23
Issue Number: 3
DOI: 10.26083/tuprints-00023912
Corresponding Links:
Origin: Secondary publication DeepGreen

Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple graph grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propagate changes from one model to the other or how to change one model in such a way that propagation is guaranteed to be possible. Restricting model synchronization to these derived rules, however, may lead to unnecessary deletion and recreation of model elements during change propagation. This is inefficient and may cause unnecessary information loss, i.e., when deleted elements contain information that is not represented in the second model, this information cannot be recovered easily. Short-cut rules have recently been developed to avoid unnecessary information loss by reusing existing model elements. In this paper, we show how to automatically derive (short-cut) repair rules from short-cut rules to propagate changes such that information loss is avoided and model synchronization is accelerated. The key ingredients of our rule-based model synchronization process are these repair rules and an incremental pattern matcher informing about suitable applications of them. We prove the termination and the correctness of this synchronization process and discuss its completeness. As a proof of concept, we have implemented this synchronization process in eMoflon, a state-of-the-art model transformation tool with inherent support of bidirectionality. Our evaluation shows that repair processes based on (short-cut) repair rules have considerably decreased information loss and improved performance compared to former model synchronization processes based on TGGs.

Uncontrolled Keywords: Bidirectional transformation, Model synchronization, Triple graph grammar, Incremental pattern matching, Change propagation
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-239124
Additional Information:

Special Issue: FASE 2019

Classification DDC: 000 Generalities, computers, information > 004 Computer science
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Real-Time Systems
Date Deposited: 30 Apr 2024 11:23
Last Modified: 30 Apr 2024 11:24
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23912
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