JENSEN, Jonnas F., Kim G. LARSEN, Jiří SRBA and Lars OESTERGAARD. Efficient Model Checking of Weighted CTL with Upper-Bound Constraints. International Journal on Software Tools for Technology Transfer (STTT). Springer-Verlag GmbH, 2016, vol. 18, No 4, p. 409-426. ISSN 1433-2779. Available from: https://dx.doi.org/10.1007/s10009-014-0359-5.
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Basic information
Original name Efficient Model Checking of Weighted CTL with Upper-Bound Constraints
Authors JENSEN, Jonnas F. (208 Denmark), Kim G. LARSEN (208 Denmark), Jiří SRBA (203 Czech Republic, guarantor, belonging to the institution) and Lars OESTERGAARD (208 Denmark).
Edition International Journal on Software Tools for Technology Transfer (STTT), Springer-Verlag GmbH, 2016, 1433-2779.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
WWW Link to publisher
Impact factor Impact factor: 1.612
RIV identification code RIV/00216224:14330/16:00089061
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1007/s10009-014-0359-5
UT WoS 000379708300005
Keywords in English CTL model checking; Kripke structure; on-the-fly algorithms; dependency graph
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/4/2017 05:43.
Abstract
We present a symbolic extension of dependency graphs by Liuand Smolka in order to model-check weighted Kripke structures againstthe logic CTL with upper-bound weight constraints. Our extension introducesa new type of edges into dependency graphs and lifts the computation offixed-points from boolean domain to nonnegative integers in order to copewith the weights. We present both global and local algorithms for thefixed-point computation on symbolic dependency graphs and argue for theadvantages of our approach compared to the direct encoding of the modelchecking problem into dependency graphs. We implement all algorithmsin a publicly available tool prototype and evaluate them on severalexperiments. The principal conclusion is that our local algorithm isthe most efficient one with an order of magnitude improvement formodel checking problems with a high number of `witnesses'.
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