Towards Understandable Guards of Extracted State Machines from Embedded Software

The extraction of state machines from complex software systems can be very useful to understand the behavior of a software, which is a prerequisite for other software activities, such as maintenance, evolution and reengineering. However, using static analysis to extract state machines from real-world embedded software often leads to models that cannot be understood by humans: The extracted models contain a high number of states and transitions and very complex guards (transition conditions). Integrating user interaction into the extraction process can reduce these state machines to an acceptable size. However, the problem of highly complex guards remains. In this paper, we present a novel approach to reduce the complexity of guards in such state machines to a degree that is understandable for humans. The conditions are reduced by a combination of heuristic logic minimization, masking of infeasible paths, and using transition priorities. The approach is evaluated with software developers on industrial embedded C code. The results show that the approach is highly effective in making the guards understandable. Our controlled experiment shows that guards reduced by our approach and presented with priorities are easier to understand than guards without priorities.