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 [1,3], 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 continuous-time Markov chain, so that model checking procedures for CSL [3,2] can be employed.