A Survey of Triple Graph Grammar Tools (bibtex)
Reference:
, "A Survey of Triple Graph Grammar Tools", in Bidirectional Transformations, vol. 57, pp. 1-18, EC-EASST, 2013.
Abstract:
Model transformation plays a central role in Model-Driven Engineering (MDE) and supporting bidirectionality is a current challenge with important applications. Triple Graph Grammars (TGGs) are a formally founded, bidirectional model transformation language shown by numerous case studies to be promising and useful in practice. TGGs have been researched for more than 15 years and multiple TGG tools are under active development. Although a common theoretical foundation is shared, TGG tools differ considerably concerning expressiveness applicability, efficiency, and the underlying translation algorithm. There currently exists neither a quantitative nor a qualitative overview and comparison of TGG tools and it is quite difficult to understand the different foci and corresponding strengths and weaknesses. Our contribution in this paper is to develop a set of criteria for comparing TGG tools and to provide a concrete quantitative and qualitative comparison of three TGG tools.
Links:
[bibtex] [url]
@InCollection{HLG13+,
AUTHOR = {Hildebrandt, Stephan and Lambers, Leen and Giese, Holger and Rieke, Jan and Greenyer, Joel and Sch\"{a}fer, Wilhelm and Lauder, Marius and Anjorin, Anthony and Sch\"{u}rr, Andy},
TITLE = {{A Survey of Triple Graph Grammar Tools}},
YEAR = {2013},
BOOKTITLE = {Bidirectional Transformations},
VOLUME = {57},
PAGES = {1-18},
PUBLISHER = {EC-EASST},
URL = {http://journal.ub.tu-berlin.de/eceasst/article/view/865/858},
OPTacc_url = {},
PDF = {uploads/pdf/OL10_1.pdf},
OPTacc_pdf = {},
ABSTRACT = {Model transformation plays a central role in Model-Driven Engineering (MDE) and supporting bidirectionality is a current challenge with important applications. Triple Graph Grammars (TGGs) are a formally founded, bidirectional model transformation language shown by numerous case studies to be promising and useful in practice. TGGs have been researched for more than 15 years and multiple TGG tools are under active development. Although a common theoretical foundation is shared, TGG tools differ considerably concerning expressiveness applicability, efficiency, and the underlying translation algorithm. There currently exists neither a quantitative nor a qualitative overview and comparison of TGG tools and it is quite difficult to understand the different foci and corresponding strengths and weaknesses. Our contribution in this paper is to develop a set of criteria for comparing TGG tools and to provide a concrete quantitative and qualitative comparison of three TGG tools.}
}
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