Abstract
Fast and competitive software industry demands rapid development using Component Based Software Development (CBSD). CBSD is dependent on the availability of the high-quality reusable component libraries. Recently, evolutionary multi-objective optimization algorithms have been used to identify sets of reusable software components from the source-code of Object Oriented (OO) software, using different quality indicators (e.g. cohesion, coupling, etc.). Sometimes, these used quality indicators are quite sensitive towards the small variations in their values, although they should not be. Therefore, this paper analyzes the sensitivity of the evolutionary technique for three quality indicators used during the identification: Frequent Usage Pattern (FUP), Semantic and evolutionary coupling. The sensitivity analysis is performed on three widely used open-source OO software. The experimentation is performed by mutating the system to different degrees. Results of the empirical analysis indicate that the semantic parameter is most sensitive and important. Ignoring this feature highly degrades the quality; FUP relation is uniformly sensitive and evolutionary relations's sensitivity is non-uniform.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.