Paper Info
Title
MOOGLE: A Model Search Engine
Abstract
Models are becoming increasingly important in the software 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
2008
10.1007/978-3-540-87875-9_22
Model Driven Engineering Languages and Systems
Keywords
Field
DocType
efficient mechanism,various existing search engine,model search engine,metamodel information,text-based search,software process,complex query,richer search index,search engine
Metasearch engine,Search engine,Information retrieval,Semantic search,Computer science,Search engine indexing,Search-oriented architecture,Search analytics,Metamodeling,Search-based software engineering
Conference
Volume
ISSN
Citations 
5301
0302-9743
29
PageRank 
References 
Authors
1.20
14
3
Name
Order
Citations
PageRank
Daniel Lucrédio121916.11
Renata Pontin de Mattos Fortes227335.10
Jon Whittle32929162.07