摘要
To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic （PLTL） model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata （NA） in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms （NFs）, next constructs Normal Form Graphs （NFGs） for NF formulas, and it fi- nally transforms NFGs into the NA which ac- cepts both finite words and int-mite words. The experimental data show that the new algorithm re- duces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indi- cate that the PLTL model checking technique em- ploying the new algorithm generates a smaller state space in verification of concurrent systems.
To combat the well-known state-space explosion problem in Propositional Linear Temporal Logic (PLTL) model checking, a novel algorithm capable of translating PLTL formulas into Nondeterministic Automata (NA) in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms (NFs), next constructs Normal Form Graphs (NFGs) for NF formulas, and it finally transforms NFGs into the NA which accepts both finite words and infinite words. The experimental data show that the new algorithm reduces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indicate that the PLTL model checking technique employing the new algorithm generates a smaller state space in verification of concurrent systems.
基金
The first author of this paper would like to thank the follow- ing scholars, Prof. Joseph Sifakis, 2007 Turing Award Winner, for his invaluable help with my research and Dr. Kevin Lu at Brunel University, UK for his excellent suggestions on this paper. This work was supported by the National Natural Sci- ence Foundation of China under Grant No.61003079
the Chi- na Postdoctoral Science Foundation under Grant No. 2012M511588.
