Joint Optimization of Software Warranty, Patch and Price Considering Learning Effects

In general, residual faults still exist in the software after testing phase. Within the warranty period, the developers will remove the faults identified by users and release patches to improve software reliability. In this study, the learning effects of faults detection by users are considered and a warranty-patch-price joint optimization model for software is established. The effects of faults coverage rate on both software reliability and demand function are considered in this model. The optimal warranty-patch-price combination is obtained by maximizing total expected profits of the developers over software warranty period. Case study is implemented to illustrate the validity of the joint optimization model. It shows that the joint optimization can achieve the greatest profit for the developers compared with the individual optimization plans.