Quantitative Model Checking Sample Clauses

Quantitative Model Checking. Conventional model checking as introduced in the 1980’s by Clarke, Emerson, Queille and Sifakis [14, 29] is a fully automated technique to verify properties of interest of the system under consideration. However, most often real-world systems tend to involve stochastic and timed behavior. For example, hardware components inside a system may fail with a given probability or it might be of crucial interest that the system satisfies certain timing constraints. As the models for qualitative model checking abstract from numerical phenomena, there is virtually no way of analyzing quantitative properties. Quantitative model checking extends conventional model checking in a way that enables formal analysis of models involving quantitative aspects. Besides the aforementioned correctness analysis this also includes performance and dependability – often combined as performability – measures such as the time needed to reach a given goal [18]. Quantitative model checking is a push-button technique which is typically restricted to finite state models. This does, however, not mean that it is not possible to model real-valued phenomena. On the contrary: there exist formalisms that support real-valued quantities such as time despite having a finite state representation. We will now focus on real-time models, because performance analysis of GPGPU programs is one of the primary goals of the CARP project. Quantitative Model Classes. There exist various models to formally capture timed or stochas- tic behavior. Alur and Xxxx proposed Timed Automata (TA) [3] as a means to model the behavior of real-time systems over time. Formally, TA are a finite-state representation of an underlying infinite transition system. The state space of the timed automaton is given by a set of locations in which time can pass unless the invariant of the state is violated. The time that passed increases the values of the finitely many clocks associated with the automaton. Transitions between locations are guarded by conditions over these clocks and may thus only be taken when all conditions are met. Upon taking a transition, it may reset any number of clocks before entering the target state. While timed automata elegantly reflect real-time behavior, choices during the execution of the original system can only be modeled by non-determinism. In the absence of information about these choices that may be appropriate, but otherwise this represents a rather harsh abstraction. Drawing inspiration from Markov...
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