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A Summary of ReVision: History-based Model Repair Recommendations

Autor(en):
Ohrndorf, Manuel [DBLP] ;
Pietsch, Christopher [DBLP] ;
Kelter, Udo [DBLP] ;
Grunske, Lars [DBLP] ;
Kehrer, Timo [DBLP]
Zusammenfassung
This work reports recent research results on history-based model repair recommendations in Model-Driven Engineering (MDE), originally published in Reference [Oh21]. Models in MDE are primary development artifacts that are heavily edited in all software development stages and can become temporarily inconsistent during editing. Model repair tools can support developers by proposing a list of the most promising repairs. Such repair recommendations will only be accepted in practice if the generated proposals are plausible and understandable and the set as a whole is manageable. Our interactive repair tool ReVision [Oh18], aims at generating repair proposals for inconsistencies introduced by past incomplete edit steps. Such an incomplete edit step is either undone or extended to the full execution of a consistency-preserving edit operation. We evaluate our approach using histories of real-world models from popular open-source modeling projects. Our experimental results confirm our hypothesis that most of the inconsistencies can be resolved by complementing incomplete edits. In fact, 92.2% of the proposed complementations could be observed in the model history.
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Ohrndorf, M., Pietsch, C., Kelter, U., Grunske, L. & Kehrer, T., (2023). A Summary of ReVision: History-based Model Repair Recommendations. In: Engels, G., Hebig, R. & Tichy, M. (Hrsg.), Software Engineering 2023. Bonn: Gesellschaft für Informatik e.V.. (S. 99-100).
@inproceedings{mci/Ohrndorf2023,
author = {Ohrndorf, Manuel AND Pietsch, Christopher AND Kelter, Udo AND Grunske, Lars AND Kehrer, Timo},
title = {A Summary of ReVision: History-based Model Repair Recommendations},
booktitle = {Software Engineering 2023},
year = {2023},
editor = {Engels, Gregor AND Hebig, Regina AND Tichy, Matthias} ,
pages = { 99-100 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-726-5
ISSN: 1617-5468
Datum: 2023
Sprache: en (en)
Typ: Text/Conference Paper

Keywords

  • model-driven software engineering
  • model repair
  • consistency
  • recommendations
  • history analysis
Sammlungen
  • P332 - Software Engineering 2023 [60]

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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.