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Title |
Automatic Categorization of Software Modules |
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Author |
Parvinder Singh Sandhu, Madhu Bala, Hardeep Singh |
| Citation |
Vol. 7 No. 8 pp. 114-119 |
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Abstract |
The world of software has demonstrated the remarkable appeal of communal software development. Large number of software projects can leverage, reuse, and coordinate their work through internet and web-based technology. For example, Source-Forge currently hosts about sixty thousand software systems, similar strategies have suggested for corporate software development. With thousands of projects, manually locating related projects can be difficult. Hence to use automatic software categorization to find clusters of related software projects using only the source code from projects, automatic categorization of software experiments with a set of programs. Automatic categorization of software systems is a novel and intriguing challenge on software archive. Evolution has focused on determining intra-component relations of given software system also increase to differentiate between categories. Function oriented produces better result than the object oriented. Automatic categorization of software has provided better results than LSA retrieval techniques in terms of Precision and Recall with multinomial Na?ve Bayes scheme has outperformed all other approaches and shows better results than the existing approach (SVD), being used by some open source code repositories e.g. Source forge Hence, the tool can also be utilized for the automatic categorization of software components and this kind of automation may improve. |
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Keywords |
LSA, SVD, Machine Learning |
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