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Software Engineering Journal
C4.5: programs for machine learning
C4.5: programs for machine learning
Computer
IEEE Transactions on Knowledge and Data Engineering
Text categorization based on k-nearest neighbor approach for web site classification
Information Processing and Management: an International Journal
What's the code?: automatic classification of source code archives
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic Categorization Algorithm for Evolvable Software Archive
IWPSE '03 Proceedings of the 6th International Workshop on Principles of Software Evolution
Toward a Software Testing and Reliability Early Warning Metric Suite
Proceedings of the 26th International Conference on Software Engineering
MUDABlue: An Automatic Categorization System for Open Source Repositories
APSEC '04 Proceedings of the 11th Asia-Pacific Software Engineering Conference
An Information Retrieval Approach to Concept Location in Source Code
WCRE '04 Proceedings of the 11th Working Conference on Reverse Engineering
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
XSEarch: a semantic search engine for XML
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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Classification of software artifacts, in particularly the source code files, are currently performed by administrator of a repository. Even though there exist automated classification on these repositories, nevertheless existing approach focuses on semantic analysis of keywords found in the artifact. This paper presents the use of structural information, that is the software metrics, in determining the appropriate application domain for a particular artifact. Results obtained from the study show that there is a difference in the metrics' trend between files of different application domain. It is also learned that results obtained using k-nearest neighborhood outperformed C4.5 decision tree and the one generated based on Discriminant Analysis in classifying files of database and graphics domain.