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In directed model checking, the traversal of the state space is guided by an estimate of the distance from the current state to the nearest error state. This paper presents a distance-preserving abstraction for concurrent systems that allows one to compute an interesting estimate of the error distance without hitting the state explosion problem. Our(More)
Systems and protocols combining concurrency and infinite state space occur quite often in practice, but are very difficult to verify automatically. At the same time, if the system is correct, it is desirable for a verifier to obtain not a simple " yes " answer, but some independently checkable certificate of correctness. We present SLAB — the first(More)
UPPAAL/DMC is an extension of UPPAAL which provides generic heuristics for directed model checking. In this approach, the traversal of the state space is guided by a heuristic function which estimates the distance of a search state to the nearest error state. Our tool combines two recent approaches to design such estimation functions. Both are based on(More)
We propose novel controller synthesis techniques for probabilistic systems modelled using stochastic two-player games: one player acts as a controller, the second represents its environment, and probability is used to capture uncertainty arising due to, for example, unreliable sensors or faulty system components. Our aim is to generate robust controllers(More)
In this thesis, we introduce subsequence invariants, a new class of invariants for the specification and verification of systems. Unlike state invariants, which refer to the state variables of the system, subsequence invariants characterize the behavior of a concurrent system in terms of the occurrences of sequences of synchronization events. The first type(More)
We consider models of programs that incorporate probability, dense real-time and data. We present a new abstraction refinement method for computing minimum and maximum reachability probabilities for such models. Our approach uses strictly local refinement steps to reduce both the size of abstractions generated and the complexity of operations needed, in(More)
Quantitative verification is an established automated technique that can ensure predictability and dependability of software systems which exhibit probabilistic behaviour. Since offline usage of quantitative verification is infeasible for large-scale complex systems that continuously adapt to the changing environment, quantitative runtime verification was(More)
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