MOOGLE: A metamodel-based model search engine

Daniel Lucrédio, Renata P. Renata, Jon Whittle

Research output: Contribution to journalArticleResearchpeer-review

30 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)183-208
Number of pages26
JournalSoftware and Systems Modeling
Volume11
Issue number2
DOIs
Publication statusPublished - May 2012
Externally publishedYes

Keywords

  • Model reuse
  • Model search
  • Model-driven development

Cite this