A type-based HFL model checking algorithm
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 11893 LNCS, Page: 136-155
2019
- 5Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Conference Paper Description
Higher-order modal fixpoint logic (HFL) is a higher-order extension of the modal μ-calculus, and strictly more expressive than the modal μ-calculus. It has recently been shown that various program verification problems can naturally be reduced to HFL model checking: the problem of whether a given finite state system satisfies a given HFL formula. In this paper, we propose a novel algorithm for HFL model checking: it is the first practical algorithm in that it runs fast for typical inputs, despite the hyper-exponential worst-case complexity of the HFL model checking problem. Our algorithm is based on Kobayashi et al.’s type-based characterization of HFL model checking, and was inspired by a saturation-based algorithm for HORS model checking, another higher-order extension of model checking. We prove the correctness of the algorithm and report on an implementation and experimental results.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85076687876&origin=inward; http://dx.doi.org/10.1007/978-3-030-34175-6_8; http://link.springer.com/10.1007/978-3-030-34175-6_8; http://link.springer.com/content/pdf/10.1007/978-3-030-34175-6_8; https://dx.doi.org/10.1007/978-3-030-34175-6_8; https://link.springer.com/chapter/10.1007/978-3-030-34175-6_8
Springer Science and Business Media LLC
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