.png){kind=icon}
.png){kind=icon}
Return
Prioritisation of code clones using a genetic algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.infsof.2024.107443.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Context: Code clones are prevalent, and due to their diverse impact on projects' quality they require a proper management strategy. Objectives: Develop GA-based Refactoring-Aware Detection (RAD) approach for prioritisation of code clones. Method: A genetic algorithm (GA) that balances estimated gain and cost/risk of refactoring to select the optimal clone candidate to refactor. Results: GA converges on a solution, with diverse variance. The value of fitness function is higher for multi-objective approaches, but they also exhibit higher variance. Conclusion: GA can be effectively applied for clone prioritising.
Keywords:
Code duplicates
Code clones
Genetic algorithm
Clone refactoring
Clone prioritisation
Journal
IF:
4.3
Papers:
3.7K
Citations:
7.7K