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2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) (2017)
Urbana, IL, USA
Oct. 30, 2017 to Nov. 3, 2017
ISBN: 978-1-5386-3976-4
pp: 913-918
Christopher Pietsch , Software Engineering Group, University of Siegen, Germany
Manuel Ohrndorf , Software Engineering Group, University of Siegen, Germany
Udo Kelter , Software Engineering Group, University of Siegen, Germany
Timo Kehrer , Department of Computer Science, Humboldt-University of Berlin, Germany
ABSTRACT
Model slicers are tools which provide two services: (a) finding parts of interest in a model and (b) displaying these parts somehow or extract these parts as a new, autonomous model, which is referred to as slice or sub-model. This paper focuses on the creation of editable slices, which can be processed by model editors, analysis tools, model management tools etc. Slices are useful if, e.g., only a part of a large model shall be analyzed, compared or processed by time-consuming algorithms, or if sub-models shall be modified independently. We present a new generic incremental slicer which can slice models of arbitrary type and which creates slices which are consistent in the sense that they are editable by standard editors. It is built on top of a model differencing framework and does not require additional configuration data beyond those available in the differencing framework. The slicer can incrementally extend or reduce an existing slice if model elements shall be added or removed, even if the slice has been edited meanwhile. We demonstrate the usefulness of our slicer in several scenarios using a large UML model. A screencast of the demonstrated scenarios is provided at http://pi.informatik.uni-siegen.de/projects/SiLift/ase2017.
INDEX TERMS
Unified modeling language, Adaptation models, Tools, Servers, Load modeling, Computational modeling, Data models
CITATION

C. Pietsch, M. Ohrndorf, U. Kelter and T. Kehrer, "Incrementally slicing editable submodels," 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE), Urbana, IL, USA, 2017, pp. 913-918.
doi:10.1109/ASE.2017.8115704
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