MOOGLE: a metamodel-based model search engine

Autor(es)

Lucredio, Daniel ^[1] ; Fortes, Renata P. de M. ^[2] ; Whittle, Jon ^[3]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Carlos, Dept Comp, BR-13565905 Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Inst Math & Comp Sci, BR-13560970 Sao Carlos, SP - Brazil

^[3] Univ Lancaster, InfoLab21, Dept Comp, Lancaster LA1 4WA - England

• Tipo de documento: Artigo Científico
• Fonte: Software and Systems Modeling; v. 11, n. 2, p. 183-208, MAY 2012.
• Citações Web of Science: 8

Resumo

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. (AU)

• Processo FAPESP: 08/11476-8 - Estratégias para migração automática de código no contexto do desenvolvimento orientado a modelos
• Beneficiário: Daniel Lucrédio
• Linha de fomento: Bolsas no Brasil - Pós-Doutorado