DACA, Przemyslaw, Thomas A. HENZINGER, Jan KŘETÍNSKÝ and Tatjana PETROV. Faster Statistical Model Checking for Unbounded Temporal Properties. In Tools and Algorithms for the Construction and Analysis of Systems - 22nd International Conference, TACAS 2016. Berlin Heidelberg: Springer. p. 112-129. ISBN 978-3-662-49673-2. doi:10.1007/978-3-662-49674-9_7. 2016.
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Basic information
Original name Faster Statistical Model Checking for Unbounded Temporal Properties
Authors DACA, Przemyslaw (616 Poland), Thomas A. HENZINGER (40 Austria), Jan KŘETÍNSKÝ (203 Czech Republic, guarantor, belonging to the institution) and Tatjana PETROV (688 Serbia).
Edition Berlin Heidelberg, Tools and Algorithms for the Construction and Analysis of Systems - 22nd International Conference, TACAS 2016, p. 112-129, 18 pp. 2016.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/16:00088469
Organization unit Faculty of Informatics
ISBN 978-3-662-49673-2
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-662-49674-9_7
UT WoS 000406428000007
Keywords in English statistical model checking; verification; temporal logic
Tags core_A, firank_A, formela-conference
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 1/6/2022 12:34.
Abstract
We present a new algorithm for the statistical model checking of Markov chains with respect to unbounded temporal properties, including full linear temporal logic. The main idea is that we monitor each simulation run on the fly, in order to detect quickly if a bottom strongly connected component is entered with high probability, in which case the simulation run can be terminated early. As a result, our simulation runs are often much shorter than required by termination bounds that are computed a priori for a desired level of confidence on a large state space. In comparison to previous algorithms for statistical model checking our method is not only faster in many cases but also requires less information about the system, namely, only the minimum transition probability that occurs in the Markov chain. In addition, our method can be generalised to unbounded quantitative properties such as mean-payoff bounds.
Links
GBP202/12/G061, research and development projectName: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Acronym: CE-ITI)
Investor: Czech Science Foundation
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