A Mathematical Approach to Design Verification Strategies That Incorporate Corrective Activities as Dedicated Decisions

Abstract

System verification activities (VAs) are used to identify potential errors and corrective activities (CAs) are used to eliminate those errors. However, existing math-based methods to plan verification strategies do not consider decisions to implement VAs and perform CA jointly, ignoring their close interrelationship. In this article, we present a joint verification–correction model to find optimal joint verification–correction strategies (JVCSs). The model is constructed so that both VAs and CAs can be chosen as dedicated decisions with their own activity spaces. We adopt the belief model of Bayesian networks to represent the impact of VAs and CAs on verification planning and use three value factors to measure the performance of JVCSs. Moreover, we propose an order-based backward induction approach to solve for the optimal JVCS by updating all verification state values. A case study was conducted to show that our model can be applied to effectively solve the verification planning problem.