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Auflistung nach Autor:in "Mayerhofer, Tanja"

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  • ConferencePaper
    Behavioral Interfaces for Executable DSLs
    (Software Engineering 2021, 2021) Leroy, Dorian; Bousse, Erwan; Wimmer, Manuel; Mayerhofer, Tanja; Combemale, Benoit; Schwinger, Wieland
    This work summarizes our paper [Le20] originally published in the Journal of Software and Systems Modeling in 2020 about a novel language engineering approach.
  • Konferenzbeitrag
    On the Usage of UML: Initial Results of Analyzing Open UML Models
    (Modellierung 2014, 2014) Langer, Philip; Mayerhofer, Tanja; Wimmer, Manuel; Kappel, Gerti
    While UML is recognized as the de-facto standard in modeling software systems, it is at the same time often criticized for being too large and complex. To be able to evolve UML to overcome this criticism, evidence is needed about which parts of UML are actually used. In this respect, a few studies exist that investigate which diagram types of UML are commonly used. However, to the best of our knowledge, in none of these studies, evidence is provided about which modeling concepts of UML are used. Thus, we quantitatively analyze UML models to determine on a fine granularity level the usage frequency of the modeling concepts provided by UML. In this paper, we present initial results of our analysis of 121 open UML models and compare our findings with the results reported in related studies about the usage of UML.
  • Konferenzbeitrag
    Semantic model differencing based on execution traces
    (Software-engineering and management 2015, 2015) Mayerhofer, Tanja; Langer, Philip; Kappel, Gerti
    Managing the evolution of software artifacts is a crucial issue in software engineering. As in the software engineering paradigm model-driven engineering (MDE), the main software artifacts are models, managing the evolution of models constitutes a key concern in MDE. One important technique in this realm is model differencing, which is concerned with identifying differences among different versions of models. While the majority of existing model differencing approaches use a purely syntactic approach, we propose an approach that takes the semantics of models into account. In particular, our approach utilizes the behavioral semantics of the used modeling language to execute the models to be compared and obtain execution traces constituting the models' semantic interpretation. By comparing the obtained execution traces, semantic differences among the models are identified.