MARS: A metamodel recovery system using grammar inference

Authors:
Faizan Javed;Marjan Mernik;Jeff Gray;Barrett R. Bryant
Affiliations:
Department of Computer & Information Sciences, University of Alabama at Birmingham, 1300 University Boulevard, Birmingham, AL 35294-1170, USA;Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia;Department of Computer & Information Sciences, University of Alabama at Birmingham, 1300 University Boulevard, Birmingham, AL 35294-1170, USA;Department of Computer & Information Sciences, University of Alabama at Birmingham, 1300 University Boulevard, Birmingham, AL 35294-1170, USA
Venue:
Information and Software Technology
Year:
2008

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Abstract

Domain-specific modeling (DSM) assists subject matter experts in describing the essential characteristics of a problem in their domain. When a metamodel is lost, repositories of domain models can become orphaned from their defining metamodel. Within the purview of model-driven engineering, the ability to recover the design knowledge in a repository of legacy models is needed. In this paper we describe MARS, a semi-automatic grammar-centric system that leverages grammar inference techniques to solve the metamodel recovery problem. The paper also contains an applicative case study, as well as experimental results from the recovery of several metamodels in diverse domains.