Abstract
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.
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