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Title: Generating Instance Models from Meta Models.
Authors: Ehrig, Karsten
Küster, Jochen M.
Taentzer, Gabriele
First Published: 1-Jul-2008
Publisher: Springer Verlag (Germany).
Citation: Software and Systems Modeling, 2008, Online First.
Abstract: Meta modeling is a wide-spread technique to define visual languages, with the UML being the most prominent one. Despite several advantages of meta modeling such as ease of use, the meta modeling approach has one disadvantage: It is not constructive, i.e., it does not offer a direct means of generating instances of the language. This disadvantage poses a severe limitation for certain applications. For example, when developing model transformations, it is desirable to have enough valid instance models available for largescale testing. Producing such a large set by hand is tedious. In the related problem of compiler testing, a string grammar together with a simple generation algorithm is typically used to produce words of the language automatically. In this paper, we introduce instance-generating graph grammars for creating instances of meta models, thereby overcoming the main deficit of the meta modeling approach for defining languages.
DOI Link: 10.1007/s10270-008-0095-y
ISSN: 1619-1366
ISBN: 978-3-540-34893-1
Type: Article
Description: This is the author’s final draft of the paper published as Software and Systems Modeling, 2008, Online First. The original publication is available at, Doi: 10.1007/s10270-008-0095-y. The paper is also published in the book, Generating Instance Models from Meta Models, Doi: 10.1007/11768869_13.
Appears in Collections:Published Articles, Dept. of Computer Science

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