Bakir, M.E. orcid.org/0000-0002-3012-8713, Gheorghe, M., Konur, S. et al. (1 more author) (2017) Comparative Analysis of Statistical Model Checking Tools. In: Membrane Computing: 17th International Conference, CMC 2016, Milan, Italy, July 25-29, 2016, Revised Selected Papers. 17th International Conference on Membrane Computing (CMC17), 25/07/2016-29/07/2016, Milan, Italy. Lecture Notes in Computer Science, 10105 . Springer Verlag ISBN 978-3-319-54071-9
Abstract
Statistical model checking is a powerful and flexible approach for formal verification of computational models like P systems, which can have very large search spaces. Various statistical model checking tools have been developed, but choosing between them and using the most appropriate one requires a significant degree of experience, not only because different tools have different modelling and property specification languages, but also because they may be designed to support only a certain subset of property types. Furthermore, their performance can vary depending on the property types and membrane systems being verified. In this paper we evaluate the performance of various common statistical model checkers against a pool of biological models. Our aim is to help users select the most suitable SMC tools from among the available options, by comparing their modelling and property specification languages, capabilities and performances.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer 2017. This is an author produced version of a paper subsequently published in Membrane Computing: 17th International Conference, CMC 2016, Milan, Italy, July 25-29, 2016, Revised Selected Papers. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Membrane computing; P systems; Statistical model checking; Biological models; Performance benchmarking |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 May 2017 11:54 |
Last Modified: | 23 Mar 2018 22:43 |
Published Version: | https://doi.org/10.1007/978-3-319-54072-6_8 |
Status: | Published |
Publisher: | Springer Verlag |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-54072-6_8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116497 |