Verification of SPL Feature Tree by Using Bayesian Network

Abstract

Products with new features need to be introduced on the market in a prompt step and organizations need to speed up their development process. Reuse has been suggested as a solution, but to achieve effective reuse within an organization a planned and preemptive effort must be used. Software Product lines are the most promising technique and it increases productivity and software quality and decreases time-to-market. In SPL, a feature tree shows various types of features and seizures the relationships among them. Bayesian Network is gaining much interest in Software Engineering, mainly in calculating software defects and software reliability. It can make notable consequence on feature analysis & its component. This thesis applies BN in modeling and analyzing features in a feature tree. Many feature analysis are modeled and verified in Bayesian Network. The verification of the rules define the analysis rules & its correctness. Finally a tool is used for reduced human error to make result more efficient & precise.