A method for identifying software components based on Non-dominated Sorting Genetic Algorithm

Identifying the appropriate software components in the software design phase is a vital task in the field of software engineering and is considered as an important way to increase the software maintenance capability. Nowadays, many methods for identifying components such as graph partitioning and clustering are presented, but most of these methods are based on expert opinion and have poor accuracy. One of the reasons for inaccuracy of the component identification methods is the lack of attention to the fact that there are contradictions between the criteria used to recognizing a component, which to be compromised during the identification process. In this paper, a novel method based on non-dominated sorting genetic algorithm (NSGAII) is proposed to map the software component detection problem into a multi-objective optimization one. The proposed method uses the criteria of cohesions, coupling and complexity in order to identify the appropriate components. In this paper, a real study system (customers club) has been used to evaluate the proposed method. The results of the evaluation revealed that the use of the proposed multi-objective algorithm has been able to perform better than previous single-objective methods.