Artículos de revistas
MOOGLE: a metamodel-based model search engine
Fecha
2012Registro en:
SOFTWARE AND SYSTEMS MODELING, HEIDELBERG, v. 11, n. 2, pp. 183-208, MAY, 2012
1619-1366
10.1007/s10270-010-0167-7
Autor
Lucredio, Daniel
Fortes, Renata Pontin de Mattos
Whittle, Jon
Institución
Resumen
Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.