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Proposed Application of Data Mining Techniques for Clustering Software Projects
| Content Provider | Semantic Scholar |
|---|---|
| Author | Rezende, Henrique Ribeiro Esmin, Ahmed Ali Abdalla |
| Copyright Year | 2010 |
| Abstract | Software projects always generate a lot of data, ranging from informal documentation to a database with thousands of lines of code. This information extracted from software projects takes even greater when it comes to OSS (Open Source Software). Such data may include source code base, historical change in the software, bug reports, mailing lists, among others. Using data mining techniques, we can extract valuable knowledge of this set of information, thus providing improvements throughout the process of software development. The results can be used to improve the quality of software, or even to manage the project in order to obtain maximum efficiency. This article proposes the application of data mining techniques to cluster software projects, cites the advantages that can be obtained with these techniques, and illustrates the application of data mining in a Open Source Software database. |
| Starting Page | 43 |
| Ending Page | 48 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| Volume Number | 9 |
| Alternate Webpage(s) | https://flosshub.org/sites/flosshub.org/files/art06.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
