In Software Engineering, Software Development Process deals with the activities that are performed according to plan. Activities include Requirements analysis, design, coding, testing and maintenance. In coding phase code smells are identified. Code-smell is a surface indication that usually corresponds to a deeper problem in the system. If code-smells are neglected they gives path to bugs and even leads to system failure.
In existing work, Kessentini et al. used evolutionary algorithms with different adaptations for detecting code-smells. By detecting the code-smells, occurrences of bugs are reduce. Here, code-smells are considered as distributed optimization problem. In optimization process different methods are combined in parallel in order to detect code-smells. Existing work uses search based approach for detecting code smells.This approach inspects each and every line in the program for detecting the code-smells. This consumes more time.
The main aim of the proposed work is to use Particle Swarm Optimization (PSO) technique to inspect the code-smells. By using PSO technique, code-smells can be detected optimally. This improves the performance of the system.