A Hybrid approach to identify Software Reusable Components in Software Intelligence

Reusability is demarcated as the way of utilizing existing software components in software development. It plays a significant role in component-based software engineering. Extracting the components from the source code and checking the reusability factors is the most crucial part. Software Intelligence, a combination of data mining and artificial intelligence, helps to cope with the extraction and detection of reusability factor of the component. In this work prediction of reusability factor is considered. This paper proposes a hybrid PSO-NSGA III approach to detect whether the extracted component is reusable or not. The existing models lack in tuning the hyper parameters for prediction, which is considered in this work. The proposed approach was compared with four models, showing better outcomes in terms of performance metrics.