Oxford logo
[FKP12] V. Forejt, M. Kwiatkowska and D. Parker. Pareto Curves for Probabilistic Model Checking. In Proc. 10th International Symposium on Automated Technology for Verification and Analysis (ATVA'12), volume 7561 of LNCS, pages 317-332, Springer. 2012. [pdf] [bib]
Downloads:  pdf pdf (528 KB)  bib bib
Notes: An extended version of this paper, including proofs, can be found in [FKP12b]. Details of the models and properties presented in the paper are here. The original publication is available at www.springerlink.com.
Abstract. Multi-objective probabilistic model checking provides a way to verify several, possibly conflicting, quantitative properties of a stochastic system. It has useful applications in controller synthesis and compositional probabilistic verification. However, existing methods are based on linear programming, which limits the scale of systems that can be analysed and makes verification of time-bounded properties very difficult. We present a novel approach that addresses both of these shortcomings, based on the generation of successive approximations of the Pareto curve for a multi-objective model checking problem. We illustrate dramatic improvements in efficiency on a large set of benchmarks and show how the ability to visualise Pareto curves significantly enhances the quality of results obtained from current probabilistic verification tools.