We extend the learning-based automated assume guarantee paradigm to perform compositional deadlock detection. We define Failure Automata, a generalization of finite automata that accept regular failure sets. We develop a learning algorithm L{sup}F that constructs the minimal deterministic failure automaton accepting any unknown regular failure set using a minimally adequate teacher. We show how L{sup}F can be used for compositional regular failure language containment, and deadlock detection, using non-circular and circular assume guarantee rules. We present an implementation of our techniques and encouraging experimental results on several non-trivial benchmarks.
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