Derivation of stochastic reward net for compatibility and conformance verification of component erroneous behavior model

The compatibility verification between interacting components and the conformance verification of their internal behavior with the corresponding ports protocol behavior are important steps for the early identification of unexpected messages between components. The behavior models used for verification include erroneous behavior along with normal behavior, in order to ensure greater accuracy in reliability and availability analysis. We use our Component Erroneous Behavior Aspect Modeling (CeBAM) approach introduced in previous work, which applies aspect-oriented modeling for adding erroneous behavior to UML state machines representing normal behavior. In this paper we present transformation rules for deriving Stochastic Reward Net (SRN) from CeBAM representations. The first step is to generate SRN for individual component behavior in order to check the conformance between component internal behavior and their ports protocol behavior. Subsequently, we compose the generated SRNs models of the connected components to verify their compatibility. We show how to identify conformance and compatibility issues during the construction and composition of components SRN model by analyzing SRN properties (e.g., deadlocks). We illustrate the proposed verification approach through a case study modeled according to CeBAM