Qusay I., Sarhan and Ahmed, Bestoun S. and Bures, Miroslav and Kamal Z., Zamli (2022) Software module clustering: An in-depth literature analysis. IEEE Transactions on Software Engineering, 48 (6). pp. 1905-1928. ISSN 0098-5589. (Published)
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Abstract
Software module clustering is an unsupervised learning method used to cluster software entities (e.g., classes, modules, or files) with similar features. The obtained clusters may be used to study, analyze, and understand the software entities' structure and behavior. Implementing software module clustering with optimal results is challenging. Accordingly, researchers have addressed many aspects of software module clustering in the past decade. Thus, it is essential to present the research evidence that has been published in this area. In this study, 143 research papers from well-known literature databases that examined software module clustering were reviewed to extract useful data. The obtained data were then used to answer several research questions regarding state-of-the-art clustering approaches, applications of clustering in software engineering, clustering processes, clustering algorithms, and evaluation methods. Several research gaps and challenges in software module clustering are discussed in this paper to provide a useful reference for researchers in this field.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Clustering algorithms; Clustering applications; Clustering challenges; Clustering evaluation; Software module clustering; Systematic literature study |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Faculty/Division: | Faculty of Computing |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 09 Nov 2022 08:25 |
| Last Modified: | 09 Nov 2022 08:25 |
| URI: | http://umpir.ump.edu.my/id/eprint/34623 |
| Download Statistic: | View Download Statistics |
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