Improving Requirement Prioritization process in Product line using Artificial Intelligence technique

Abstract

Product families emerged a new and useful development technique in the field of software development. In Software Product Line (SPL) there are some core assets and some variants so using these assets anyone can build their desired product in very short time and effort. While working in product family’s environment we must keep an eye on the requirement prioritization
and ranking because that requirement are very important because these requirement lay the foundation of the core and variants assets which are the building blocks of SPL. So there are some major issues which we face are the more human interaction, ambiguous requirements and wrong or no requirement ranking. In this paper we proposed a framework for the ranking of
stakeholders’ requirements for the SPL’s variant and core assets using the case base reasoning CBR if available in previous use or assign them new ranking according to their requirement and their assign ranking for software product line. We evaluated our framework by empirical study. The results prove that the considerable improvement for different parameters is achieved by our framework as compared to conventional approaches of requirement prioritization.