Seminars

As an extension of word transformations, tree transformations have numerous applications in computer science : XSLT transformations, Unix packages installation and removal, databases queries... Likewise, there are many formal models to describe these transformations. However, the proof of formal properies on these models is often difficult, or even undecidable.
In this talk, I will be interested in one of the simplest model for tree transformations, namely deterministic top-down tree transducers (DTOP). It has been known for a while that the equivalence problem of DTOPs can be solved via an earliest normal form comparison algorithm, that is in 2EXPTIME. However, when applying this algorithm to practical cases, it seemed that the worst case was not bound to happen often, if ever.
I will present a new algorithm for the problem, based on the search of counterexamples via the expansion and unification of a set of rules over states of DTOPs. The most interesting feature of this algorithm is that it runs in exponential time, thus proving that the equivalence problem of DTOPs is in fact EXPTIME-complete.

Counter-Example-Guided Abstraction Refinement (CEGAR) has been very successful in model checking.
Since then, it has been applied to many different problems. It is especially proved to be a highly successful practical approach for solving the PSPACE complete QBF problem. In this paper, we propose a new CEGAR-like approach for tackling PSPACE complete problems that we call RECAR (Recursive Explore and Check Abstraction Refinement). We show that this generic approach is sound and complete. Then we propose a specific implementation of the RECAR approach to solve the modal logic K satisfiability problem. We implemented both CEGAR and RECAR approaches for the modal logic K satisfiability problem within the solver MoSaiC. We compared experimentally those approaches to the state-of-the-art solvers for that problem. The RECAR approach outperforms the CEGAR one for that problem and also compares favorably against the state-of-the-art on the benchmarks considered.