Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Fuzzy particle swarm optimization algorithm (NFPSO) for reachability analysis of complex software systems

Version 1 : Received: 12 October 2020 / Approved: 14 October 2020 / Online: 14 October 2020 (08:21:28 CEST)

How to cite: Salimi, N.; Rafe, V.; Tabrizchi, H.; Mosavi, A. Fuzzy particle swarm optimization algorithm (NFPSO) for reachability analysis of complex software systems. Preprints 2020, 2020100288 (doi: 10.20944/preprints202010.0288.v1). Salimi, N.; Rafe, V.; Tabrizchi, H.; Mosavi, A. Fuzzy particle swarm optimization algorithm (NFPSO) for reachability analysis of complex software systems. Preprints 2020, 2020100288 (doi: 10.20944/preprints202010.0288.v1).

Abstract

Nowadays, 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 meta-heuristic 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 open-source 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 meta-heuristic algorithms such as GA and the hybrid of PSO-GSA in analyzing reachability properties.

Subject Areas

Fuzzy Adaptive Particle Swarm Optimization; Graph Transformation System; Model Checking; Reachability Property; State Space Explosion

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.