Selection of human evaluators for design smell detection using dragonfly optimization algorithm: An empirical study

Design smell detection is considered an efficient activity that decreases maintainability expenses and improves software quality. Human context plays essential role in this domain. In paper, we propose a search-based approach to optimize the selection of human evaluators for design detection. For purpose, Dragonfly Algorithm (DA) employed identify optimal or near-optimal evaluator’s profiles. An online survey designed asks evaluate sample classes presence god class smell. The Kappa-Fleiss test has been used validate proposed approach. results show dragonfly optimization algorithm can be utilized effectively decrease efforts (time, cost ) concerning identification number profile experts required evaluation process. A Search-based improving god-class Consequently, leads minimizing maintenance cost.