Generalized Craig Interpolation for Stochastic Boolean Satisfiability Problems with Applications to Probabilistic State Reachability and Region Stability

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 probabilistic bounded model checking (PBMC) of symbolically represented Markov decision processes. This article identifies a notion of Craig interpolant for the SSAT framework and develops an algorithm for computing such interpolants based on a resolution calculus for SSAT. As a potential application area of this novel concept of Craig interpolation, we address the symbolic analysis of probabilistic systems. We first investigate the use of interpolation in probabilistic state reachability analysis, turning the falsification procedure employing PBMC into a verification technique for probabilistic safety properties. We furthermore propose an interpolation-based approach to probabilistic region stability, being able to verify that the probability of stabilizing within some region is sufficiently large

On the Logical Characterisation of Performability Properties

Markov-reward models, as extensions of continuous-time Markov chains, have received increased attention for the specification and evaluation of performance and dependability properties of systems. Until now, however, the specification of reward-based performance and dependability measures has been done manually and informally. In this paper, we change this undesirable situation by the introduction of a continuous-time, reward-based stochastic logic. We argue that this logic is adequate for expressing performability measures of a large variety. We isolate two important sub-logics, the logic CSL [#!ASS+96!#,#!BKH99!#], and the novel logic CRL that allows one to express reward-based properties. These logics turn out to be complementary, which is formally established in our main duality theorem. This result implies that reward-based properties expressed in CRL for a particular Markov reward model can be interpreted as CSL properties over a derived continuo us-time Markov chain, so that model checking procedures for CSL [#!BKH99!#,#!BHHK00!#] can be employed