PCTL model checking based on Giraph

Abstract

At present, ensuring system security and verifying whether the system meets the given requirements have been the focus of computer engineers. Model checking is an automatic and exhaustive technique to prove whether there has absence of such errors in a system which has been widely applied. It has a regular requirement for a system model under consideration and a desired property. Then it systematically checks whether or not the given model satisfies this property. However, the traditional algorithm on Hadoop for checking Computation Tree Logic (CTL) formula does not scale well because of the need of conducting a huge number of states with each passing day. To deal with the state space explosion problem, we propose a scalable algorithm on the platform of Giraph, which is a new rising iterative graph processing platform with high scalability and employs the Bulk Synchronous Parallel (BSP) model. We also address this problem by selecting Probabilistic Computation Tree Logic (PCTL) as the property specification, which is strictly more expressive and makes a great advancement on using probability to describe the probability of an event occurring. This paper comes up with a novel method based on Giraph to verify one PCTL formula, which is used to represent a maximum probability of reaching a certain state, being regarded as a quantitative description of a property in system detection. Owing much to the Giraph platform, our experiment is of great interest as it displays much more efficiently than current methods which are based on Hadoop and so on. Ultimately, we discover that the processing time of Giraph platform applying message model is much shorter than that of Hadoop platform applying iterative model through experimental comparison.