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Classification of Software Artifacts Based on Structural Information

  • Yuhanis Yusof
  • Omer F. Rana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6279)

Abstract

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.

Keywords

Discriminant Function Analysis Source Code Application Domain Discriminant Function Analysis Recall Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yuhanis Yusof
    • 1
  • Omer F. Rana
    • 2
  1. 1.College of Arts and Sciences, Information Technology BuildingUniversiti Utara MalaysiaSintokMalaysia
  2. 2.School of Computer ScienceCardiff UniversityCardiffUK

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