A New Heuristic for Deadlock Detection in Safety Analysis of Software Systems

The safety analysis of software systems, especially safety-critical ones, should be performed exactly because even a minor failure in these systems may result in disaster consequences. Also, such analysis must be done before implementation, i.e. the design step and in the model level. Model checking is an exact and mathematical-based way that gets a model of a system and analyzes it through exploring all reachable states of the model. Due to the complexity of some systems and their models, this way may face the state space explosion problem, i.e. it cannot explore all available states. A solution to solve this problem in these systems is that model checking tries to refute them, instead of verifying them, by finding errors such as deadlock (if available).Although, a heuristic has been previously proposed to find a deadlock in the model's state space and it has been applied in several simple heuristic search and evolutionary algorithms, its detection speed has been low. In this paper, we propose a novel heuristic to detect a deadlock in the model's state space, and test and compare its detection speed by applying it in several simple heuristic search algorithms such as iterative deepening A*, beam search, and evolutionary algorithms such as genetic, particle swarm optimization, and Bayesian optimization. Comparison results confirm that the new heuristic can detect a deadlock in less time than the previous heuristic.