Paper Info
Title
MOOGLE: a metamodel-based model search engine
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.
Year
DOI
Venue
2012
10.1007/s10270-010-0167-7
Software and System Modeling
Keywords
DocType
Volume
efficient mechanism,various existing search engine,model search engine,metamodel information,model-driven development · model search · model reuse,metamodel-based model search engine,text-based search,complex query,richer search index,software development process
Journal
11
Issue
ISSN
Citations 
2
1619-1374
16
PageRank 
References 
Authors
0.74
33
3
Name
Order
Citations
PageRank
Daniel Lucrédio121916.11
Renata Pontin M. Fortes223427.74
Jon Whittle32929162.07