Abstract
State space explosion is the main obstacle for model checking concurrent programs. Among the solutions, partial-order reduction (POR), especially dynamic partial-order reduction (DPOR) [1], is one of the promising approaches. However, DPOR only supports stateless explorations for acyclic state spaces. In this paper, we present the stateful DPOR approach for may-cyclic state spaces, which naturally combines DPOR with stateful model checking to achieve more efficient reduction. Its basic idea is to summarize the interleaving information for all transition sequences starting from each visited state, and infer the necessary partial-order information based on the summarization when a visited state is encountered again. Experiment results on two programs coming from [1] show that both of the costs of space and time could be remarkably reduced by stateful DPOR with rather reasonable extra memory overhead.
Partially supported by the National NSF of China under grant No. 60233020, National Hi-Tech Programme of China under the grant 2005AA113130 and Program for New Century Excellent Talents in University under grant No. NCET-04-0996.
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Yi, X., Wang, J., Yang, X. (2006). Stateful Dynamic Partial-Order Reduction. In: Liu, Z., He, J. (eds) Formal Methods and Software Engineering. ICFEM 2006. Lecture Notes in Computer Science, vol 4260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11901433_9
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DOI: https://doi.org/10.1007/11901433_9
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