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A Genetic Algorithm Based Approach for Event Synchronization Analysis in Real-Time Embedded Systems

In real-time embedded systems, due to race conditions, synchronization order between events may be different from one execution to another. This behavior is permissible as in concurrent systems, but should be fully analyzed to ensure the correctness of the system. In this paper, a new intelligent method is presented to analyze event synchronization sequence in embedded systems. Our goal is to identify the feasible sequence, and to determine timing parameters that lead to these sequences. Our approach adopts timed event automata (TEA) to model the targeted embedded system and use a race condition graph (RCG) to specify event synchronization sequence (SYN-Spec). A genetic algorithm working with simulation is used to analyze the timing parameters in the target model and to verify whether a defined SYN-Spec is satisfied or not. A case study shows that the method proposed is able to find potential execution sequences according to the event synchronization orders.