Using fairness to make abstractions work

Abstractions often introduce infinite traces which have no corresponding traces at the concrete level and can lead to the failure of the verification. Refinement does not always help to eliminate those traces. In this paper, we consider a timer abstraction that introduces a cyclic behaviour on abstract timers and we show how one can exclude cycles by imposing a strong fairness constraint on the abstract model. By employing the fact that the loop on the abstract timer is a self-loop, we render the strong fairness constraint into a weak fairness constraint and embed it into the verification algorithm. We implemented the algorithm in the DTSpin model checker and showed its efficiency on case studies. The same approach can be used for other data abstractions that introduce self-loops

Bug hunting with false negatives

Safe data abstractions are widely used for verification purposes. Positive verification results can be transferred to the concrete system. When a property is violated in the abstract system, one still has to check whether a concrete violation exists. However, even when the violation scenario is not reproducible in the concrete system (a false negative), it may still contain information on possible sources of bugs. Here we propose a bug hunting framework based on abstract violation scenarios. We first extract a violation pattern from an abstract violation scenario. The violation pattern represents multiple violation scenarios, increasing the chance that a corresponding concrete violation exists. Then we look for a concrete violation that corresponds to the violation pattern by using constraint solving techniques

Abstractions and Static Analysis for Verifying Reactive Systems

Fokkink, W.J. [Promotor]Sidorova, N. [Copromotor

Using Fairness to Make Abstractions Work

Abstractions often introduce infinite traces which have no corresponding traces at the concrete level and may lead to failure of the verification. Refinement does not always help to eliminate those traces

Using fairness to make abstractions work

Abstractions often introduce infinite traces which have no corresponding traces at the concrete level and can lead to the failure of the verification. Refinement does not always help to eliminate those traces. In this paper, we consider a timer abstraction that introduces a cyclic behaviour on abstract timers and we show how one can exclude cycles by imposing a strong fairness constraint on the abstract model. By employing the fact that the loop on the abstract timer is a self-loop, we render the strong fairness constraint into a weak fairness constraint and embed it into the verification algorithm. We implemented the algorithm in the DTSpin model checker and showed its efficiency on case studies. The same approach can be used for other data abstractions that introduce self-loops