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Software and Systems Modeling

Erschienen in:

28.04.2015 | Regular Paper

Proactive modeling: a new model intelligence technique

verfasst von: Tanumoy Pati, Sowmya Kolli, James H. Hill

Erschienen in: Software and Systems Modeling | Ausgabe 2/2017

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Abstract

This article discusses a model intelligence technique called proactive modeling. The goal of proactive modeling is to reduce the amount of manual modeling required when using a graphical DSML and to assist in step-by-step creation of a model. Proactive modeling accomplishes this goal by examining the metamodels syntax and constraints, automatically executing model modifications, and prompting the modeler for assistance when more than one valid model modification exists, but none are necessary. We have integrated proactive modeling into the generic modeling environment (GME) as a generic add-on that can operate on any domain-specific modeling language implemented in GME. Lastly, results from applying proactive modeling to several DSMLs in GME show that it can reduce modeling effort.

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This article focuses on graphical DSMLs, but we are aware that DSMLs can be non-graphical. Our work is also not limited to only graphical DSMLs. We refer to graphical DSMLs as just DSMLs so we do not have to continually write “graphical DSMLs”.

See “Appendix” for the remaining constraints of the LMS

It is assumed that such constraint violations are not automatically checked after each model modification, which is possible in GME. Instead, it is assumed that the modeler manually invokes the constraint solver to validate the model.

A GME add-on is a domain-independent event handler that receives events dictating what model actions have occurred.

The test cases, including the GME metamodel, used in each of the scenarios can be downloaded from the following location: https://github.com/SEDS/GAME/tree/Model_Intel_Perf_Tests/performance-tests/Model_Intelligence/scalability.

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Titel: Proactive modeling: a new model intelligence technique
verfasst von: Tanumoy Pati
Sowmya Kolli
James H. Hill
Publikationsdatum: 28.04.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Software and Systems Modeling / Ausgabe 2/2017
Print ISSN: 1619-1366
Elektronische ISSN: 1619-1374
DOI: https://doi.org/10.1007/s10270-015-0465-1

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