Hybrid Model using Firefly and BBO for Feature Selection in Software Product Line

Background: Software Product Line is the group of multiple software systems that share a similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organizations. Objective: The objective of this research article is to obtain an optimized subset of features capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed; a) an improved objective function which is used to compute the contribution of each feature with weight-based methodology; and b) a hybrid model that is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results show that the proposed hybrid model outperforms the state of art me-taheuristic algorithms. © 2021 Bentham Science Publishers.