Abstract
Data mining and search-based algorithms have been applied to various problems due to their power and performance. There have been several studies on the use of these algorithms for refactoring. In this paper, we show how search based algorithms can be used for sequence diagram refactoring. We also show how a hybridized algorithm of Kmeans and Simulated Annealing (SA) algorithms can aid each other in solving sequence diagram refactoring. Results show that search based algorithms can be used successfully in refactoring sequence diagram on small and large case studies. In addition, the hybridized algorithm obtains good results using selected quality metrics. Detailed insights on the experiments on sequence diagram refactoring reveal that the limitations of SA can be addressed by hybridizing the Kmeans algorithm to the SA algorithm.
| Original language | English |
|---|---|
| Article number | e0202629 |
| Journal | PLoS ONE |
| Volume | 13 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2018 |
Bibliographical note
Funding Information:All funding support received during this specific study is given by "King Fahd University of Petroleum and Minerals". No individuals employed or contracted by the funders (other than the named authors) played any role in: study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2018 Baqais, Alshayeb. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology (all)
- Agricultural and Biological Sciences (all)
- General