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Indian Conference on Logic and Its Applications

ICLA 2017: Logic and Its Applications pp 91–105Cite as

Random Models for Evaluating Efficient Büchi Universality Checking

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10119))

Abstract

Automata-theoretic formal verification approaches the problem of guaranteeing that a program conforms to its specification by reducing conformance to language containment. We can prove conformance by representing both programs and specifications as automata and proving that the specification contains the program. This connection to the theory of automata on infinite words motivated an extensive research program into the algorithmic theory of automata on infinite words, with a focus on algorithms that perform well in practice. The focus on practical performance is important because of the large gap between worst-case complexity and practice for many automata-theoretic algorithms. Unfortunately, there are few benchmark instances of automata in industrial verification. To overcome this challenge, Tabakov and Vardi proposed a model for generating random automata as test cases.

The Tabakov-Vardi (T-V) model, however, is just one random model, based on a specific, rather simple model of random graphs. Other models of random graphs have been studied over the years. While the T-V model has the advantage of simplicity, it is not clear that performance analysis conducted on this model is robust, and an analogous analysis over other random models might yield different conclusions. To address this problem, we introduce three novel models of random automata, yielding automata that are richer in structure than the automata generated by the T-V model. By generating large corpora of random automata and using them to evaluate the performance of universality-checking algorithms, we show that the T-V model is a robust random model for evaluating performance of universality-checking algorithms.

We recommend viewing the plots in this paper online. For a longer technical report, see http://www.cs.rice.edu/~vardi.

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Notes

  1. 1.

    The full version of the paper, with more models, can be found in the technical report [3].

  2. 2.

    http://languageinclusion.org/doku.php?id=tools.

  3. 3.

    Other models can be found in the technical report [3].

  4. 4.

    http://www.rcsg.rice.edu/sharecore/davinci/.

  5. 5.

    Referred to in their paper as a “Markov graph”.

  6. 6.

    https://www.cs.rice.edu/CS/Verification/Software/software.html.

  7. 7.

    http://www.languageinclusion.org/doku.php?id=tools.

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Acknowledgements

Work supported in part by NSF grants CCF-1319459 and IIS-1527668, by NSF Expeditions in Computing project “ExCAPE: Expeditions in Computer Augmented Program Engineering”, as well as the Data Analysis and Visualization Cyberinfrastructure funded by NSF grant OCI-0959097 and Rice University.

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Authors and Affiliations

  1. Rice University, Houston, USA

    Corey Fisher & Moshe Vardi

  2. Trinity University, San Antonio, USA

    Seth Fogarty

Authors
  1. Corey Fisher
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  2. Seth Fogarty
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  3. Moshe Vardi
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Corresponding author

Correspondence to Corey Fisher .

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Editors and Affiliations

  1. Indian Statistical Institute , Chennai, Tamil Nadu, India

    Sujata Ghosh

  2. Indian Institute of Technology Delhi , New Delhi, India

    Sanjiva Prasad

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Fisher, C., Fogarty, S., Vardi, M. (2017). Random Models for Evaluating Efficient Büchi Universality Checking. In: Ghosh, S., Prasad, S. (eds) Logic and Its Applications. ICLA 2017. Lecture Notes in Computer Science(), vol 10119. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54069-5_8

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  • DOI: https://doi.org/10.1007/978-3-662-54069-5_8

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