Auflistung nach Schlagwort "model-driven software engineering"
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- KonferenzbeitragBXtendDSL: A layered framework for bidirectional model transformations combining a declarative and an imperative language (Summary)(Software Engineering 2023, 2023) Buchmann, Thomas; Bank, Matthias; Westfechtel, BernhardThis summary is based on an article which appeared in 2022 in The Journal of Systems & Software [BBW22]. Bidirectional transformations have been studied in a wide range of application domains. In modeldriven software engineering, they are required for roundtrip engineering processes. We present a pragmatic approach to engineering bidirectional model transformations that assists transformation developers by domain-specific languages, frameworks, and code generators. A thorough evaluation demonstrates conciseness, expressiveness, and scalability of our approach.
- KonferenzbeitragA Summary of ReVision: History-based Model Repair Recommendations(Software Engineering 2023, 2023) Ohrndorf, Manuel; Pietsch, Christopher; Kelter, Udo; Grunske, Lars; Kehrer, TimoThis 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.