Language Inclusion Algorithms as Complete Abstract Interpretations

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Abstract

We study the language inclusion problem (Forumala Presented). is regular. Our approach relies on abstract interpretation and checks whether an overapproximating abstraction of (Forumala Presented)., obtained by successively overapproximating the Kleene iterates of its least fixpoint characterization, is included in (Forumala Presented). We show that a language inclusion problem is decidable whenever this overapproximating abstraction satisfies a completeness condition (i.e. its loss of precision causes no false alarm) and prevents infinite ascending chains (i.e. it guarantees termination of least fixpoint computations). Such overapproximating abstraction function on languages can be defined using quasiorder relations on words where the abstraction gives the language of all words “greater than or equal to” a given input word for that quasiorder. We put forward a range of quasiorders that allow us to systematically design decision procedures for different language inclusion problems such as regular languages into regular languages or into trace sets of one-counter nets. In the case of inclusion between regular languages, some of the induced inclusion checking procedures correspond to well-known state-of-the-art algorithms like the so-called antichain algorithms. Finally, we provide an equivalent greatest fixpoint language inclusion check which relies on quotients of languages and, to the best of our knowledge, was not previously known.

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Ganty, P., Ranzato, F., & Valero, P. (2019). Language Inclusion Algorithms as Complete Abstract Interpretations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11822 LNCS, pp. 140–161). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32304-2_8

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