Parallel Randomized State-Space Search

11 years 11 months ago
Parallel Randomized State-Space Search
Model checkers search the space of possible program behaviors to detect errors and to demonstrate their absence. Despite major advances in reduction and optimization techniques, state-space search can still become cost-prohibitive as program size and complexity increase. In this paper, we present a technique for dramatically improving the costeffectiveness of state-space search techniques for error detection using parallelism. Our approach can be composed with all of the reduction and optimization techniques we are aware of to amplify their benefits. It was developed based on insights gained from performing a large empirical study of the cost-effectiveness of randomization techniques in state-space analysis. We explain those insights and our technique, and then show through a focused empirical study that our technique speeds up analysis by factors ranging from 2 to over 1000 as compared to traditional modes of state-space search, and does so with relatively small numbers of parallel p...
Matthew B. Dwyer, Sebastian G. Elbaum, Suzette Per
Added 09 Dec 2009
Updated 09 Dec 2009
Type Conference
Year 2007
Where ICSE
Authors Matthew B. Dwyer, Sebastian G. Elbaum, Suzette Person, Rahul Purandare
Comments (0)