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<!DOCTYPE html>
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<title>FLUENT Verificaiton Project</title>
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<img src="FLUENT Logo.png" alt="FLUENT Logo">
<h1>FLUENT Verification Project</h1>
<p> (FL)orida-(U)tah (E)merging and (N)ano (T)echnologies Verification Project</p>
<p><i>An Efficient Framework for the Stochastic Verification of Computation and Communication Systems Using Emerging Technologies</i>
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<h2>Funded by the National Science Foundation</h2>
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<ul class="nav">Contents
<li><a href="#line1">People</a></li>
<li><a href="#line4">Software</a></li>
<li><a href="#line5">NSF Acknowledgements</a></li>
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<p>
This research aims at advancing probabilistic verification techniques for the rigorous design of dependable systems in synthetic biology and nanotechnology. Major goals of the project include the following. First, scale up stochastic model checking with efficient and accurate state space truncation techniques. Secondly, investigate practical stochastic counterexample generation techniques and utilize them to improve the accuracy of the state reductions. Thirdly, derive automated guidance mechanisms learned from stochastic counterexamples to improve the quality and efficiency of rare-event stochastic simulations. Lastly, integrate our proposed framework within existing state-of-the-art stochastic model checking tools, PRISM and STORM; and evaluate the proposed methodology on a wide range of case studies derived from synthetic biology and nanotechnology applications. The combination of these methods into this new methodology is being explored for the first time. Altogether, this research will improve the accuracy of analysis of infinite state stochastic systems with rare-event properties.
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<li><strong>GitHub Repository : </strong> <a href="https://github.com/fluentverification" target="_blank">https://github.com/fluentverification</a></li>
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<h2 class="dark-text">Faculty<a href="#top">#back to top</a><hr></h2>
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<li><a href="http://www.async.ece.utah.edu/Myers">Chris J. Myers</a></li>
<li><a href="https://www.usf.edu/engineering/cse/people/zheng-hao.aspx">Hao Zheng</a></li>
<li><a href="https://engineering.usu.edu/ece/people/faculty/zhang-zhen">Zhen Zhang</a></li>
<li><a href="https://left.engr.usu.edu/">Chris J. Winstead</a></li>
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<h2 class="dark-text">Senior Researchers<a href="#top">#back to top</a><hr></h2>
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<li> Curtis Madsen, Ph.D., Sandia National Labs</li>
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<h2 class="dark-text">Post-Docs<a href="#top">#back to top</a><hr></h2>
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<h2 class="dark-text">Students<a href="#top">#back to top</a><hr></h2>
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<li>University of Utah / University of Colorado
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<li>Jeanet Mante</li>
<li>Lukas Buecherl</li>
<li>Pedro Fontanarrosa</li>
</ul></li>
<li>Utah State University
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<li>Thakur Neupane</li>
<li>Trent Wall</li>
<li>Riley Roberts</li>
<li>Porter Giles</li>
<li>Tom Prouty</li>
<li>Daren Swasey</li>
<li>Brett Jepsen</li>
</ul></li>
<li>University of South Florida<ul>
<li>Mohammad Ahmadi</li>
<li>Nisa</li>
<li>Laureano</li>
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<h2 class="dark-text">Software<a href="#top">#back to top</a><hr></h2>
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<h2 class="dark-text">NSF Acknowledgements<a href="#top">#back to top</a><hr></h2>
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<p>
This material is based upon work supported by the National Science Foundation under Grant Nos. 1856733, 1856740, and 1900542. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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