There are many hard verification problems that are currently only solvable by applying several verifiers that are based on complementing technologies. Conditional model checking (CMC) is a successful solution for cooperation between verification tools. In CMC, the first verifier outputs a condition describing the state space that it successfully verified. The second verifier uses the condition to focus its verification on the unverified state space. To use arbitrary second verifiers, we recently proposed a reducer-based approach. One can use the reducer-based approach to construct a conditional verifier from a reducer and a (non-conditional) verifier: the reducer translates the condition into a residual program that describes the unverified state space and the verifier can be any off-the-shelf verifier (that does not need to understand conditions). Until now, only one reducer was available. But for a systematic investigation of the reducer concept, we need several reducers. To fill this gap, we developed FRED, a Framework for exploring different REDucers. Given an existing reducer, FRed allows us to derive various new reducers, which differ in their trade-off between size and precision of the residual program. For our experiments, we derived seven different reducers. Our evaluation on the largest and most diverse public collection of verification problems shows that we need all seven reducers to solve hard verification tasks that were not solvable before with the considered verifiers.
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