Abstract
The stochastic Boolean satisfiability (SSAT) problem has been introduced by Papadimitriou in 1985 when adding a probabilistic model of uncertainty to propositional satisfiability through randomized quantification. SSAT has many applications, among them bounded model checking (BMC) of symbolically represented Markov decision processes. This paper identifies a notion of Craig interpolant for the SSAT framework and develops an algorithm for computing such interpolants based on SSAT resolution. As a potential application, we address the use of interpolation in SSAT-based BMC, turning the falsification procedure into a verification approach for probabilistic safety properties.
This work has been supported by the German Research Council (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS, www.avacs.org).
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Teige, T., Fränzle, M. (2011). Generalized Craig Interpolation for Stochastic Boolean Satisfiability Problems. In: Abdulla, P.A., Leino, K.R.M. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2011. Lecture Notes in Computer Science, vol 6605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19835-9_14
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