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Hard real-time systems such as automotive control systems have to guarantee that strict deadlines are met for applications. Recent automotive control systems have been network systems that have combined event-triggered with time-triggered networks, i.e., Controller Area Network (CAN) and FlexRay. A CAN-FlexRay gateway has to execute real-time message transfers from CAN to FlexRay and from FlexRay to CAN to guarantee that communication deadlines are met. Most gateways in the automotive control systems select messages according to the priority of the messages and pack them into frames. However, when many events of same kinds occur within the short period, the gateway cannot guarantee that communication deadlines for time-triggered and first event-triggered messages will be met because many event-triggered messages prevent time-triggered messages from being packed into frame.

To detect difficult-to-find defects in automotive control systems, we have proposed a modeling method with a program slicing technique. In this method, a verifier adjusts the boundaries of source code to be extracted on a variable dependence graph, in a kind of data flow. We have developed software tools for this method and achieved a 35% decrease in total verification time on model checking. This paper provides some consideration on effective cases of the method from verification practices. There are two types of malfunction causes: one is the timing of processes (race conditions), and the other is complex logics. Each type requires different elements in external environment models. Furthermore, we propose regression verification based on the modeling method above, to further reduce verification time on model checking. The paper outlines tool extensions needed to realize regression verification.