Learning Assumptions for CompositionalVerification of Timed Systems

Shang-Wei Lin, Etienne Andre, Yang Liu, Jun Sun, Jin Song Dong
2014 IEEE Transactions on Software Engineering  
Compositional techniques such as assume-guarantee reasoning (AGR) can help to alleviate the state space explosion problem associated with model checking. However, compositional verification is difficult to be automated, especially for timed systems, because constructing appropriate assumptions for AGR usually requires human creativity and experience. To automate compositional verification of timed systems, we propose a compositional verification framework using a learning algorithm for
more » ... orithm for automatic construction of timed assumptions for AGR. We prove the correctness and termination of the proposed learning-based framework, and experimental results show that our method performs significantly better than traditional monolithic timed model checking. Index Terms-automatic assume-guarantee reasoning, model checking, timed systems 3 1. In [7] , the comparison between the learning-based and abstractionrefinement-based approaches for generating untimed assumptions in AGR did not indicate a clear winner. Therefore, it would be interesting as well to study a similar abstraction-refinement-based approach in a timed setting.
doi:10.1109/tse.2013.57 fatcat:mfluxobznfcxbg3nvii5z3suuu