Download PDFOpen PDF in browserFuzzy Particle Swarm Optimization Algorithm (NFPSO) for Reachability Analysis of Complex Software SystemsEasyChair Preprint 432811 pages•Date: October 8, 2020AbstractNowadays, model checking is applied as an accurate technique to verify software systems. The main problem of model checking techniques is the state space explosion. This problem occurs due to the exponential memory usage by the model checker. In this situation, using metaheuristic and evolutionary algorithms to search for a state in which a property is satisfied/violated is a promising solution. Recently, different evolutionary algorithms like GA, PSO, etc. are applied to find deadlock state. Even though useful, most of them are concentrated on finding deadlock. This paper proposes a fuzzy algorithm in order to analyze reachability properties in systems specified through GTS with enormous state space. To do so, we first extend the existing PSO algorithm (for checking deadlocks) to analyze reachability properties. Then, to increase the accuracy, we employ a Fuzzy adaptive PSO algorithm to determine which state and path should be explored in each step to find the corresponding reachable state. These two approaches are implemented in an opensource toolset for designing and model checking GTS called GROOVE. Moreover, the experimental results indicate that the hybrid fuzzy approach improves speed and accuracy in comparison with other techniques based on metaheuristic algorithms such as GA and the hybrid of PSOGSA in analyzing reachability properties. Keyphrases: Fuzzy Adaptive Particle Swarm Optimization, Graph Transformation System, model checking, reachability property, state space explosion
