L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL modelchecking based on negative cycle detection. In Proceedings of 21st Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'01), Lecture Notes in Computer Science. Springer, Dec. 2001. Home/Search Document Details and Download
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Random Walk Based Heuristic Algorithms for Distributed.. - Sivaraj, Gopalakrishnan (2003) (3 citations) (Correct)
....[CVWY92, HPY96] algorithm employed to detect accepting (violating) B uchi automaton cycles. This is to be expected because depth first search has been proved to be inherently sequential [Reif85] Their paper reports feasibility (without actual examples) on a nine node 366MHz Pentium cluster. In [BCKP01], B uchi acceptance is reduced to detecting negative cycles (those that have a negative sum of edge weights) in a weighted directed graph. This reduction is achieved by attaching an edge weight of 1 to all outgoing edges out of an accepting state, and a weight of 0 to all other edges. Despite ....
L. Brim, I. Cerna, P. Krcal, R. Pelanek, "Distributed LTL model checking based on negative cycle detection", in Proceedings of the FSTTCS Conference, Bangalore, India, December 2001.
Local Parallel Model Checking for the Alternation-Free.. - Bollig, Leucker, Weber (2002) (4 citations) (Correct)
....single computer can be employed to sequentially handle one task at a time. In [5] we presented a parallel algorithm for a fragment of L . 12] introduced a symbolic parallel algorithm for the full calculus. However, both are global so that the transition system has to be constructed totally. [6] presents a model checking algorithm for LTL using a costly parallel cycle detection. Confer [4] for further related work. Our main contribution is the first local parallel model checking algorithm for L that supports interactive debugging and omits a cycle detection, which allows a powerful ....
L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL model-checking based on negative cycle detection. In Proc. of 21st Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'01), LNCS. Springer, Dec. 2001. This is also the reason why we did not optimise our algorithm wrt. an a-priori-known transition systems.
LTL Model Checking - Pelánek (2003) Self-citation (Brim Cern Pel) (Correct)
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L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL model checking based on negative cycle detection. In Proc. Foundations of Software Technology and Theoretical Computer Science, volume 2245 of LNCS, pages 96-107. Springer, 2001.
Distributed Explicit Fair Cycle Detection - Cerna, Pelane (2003) (4 citations) Self-citation (Cern Pel) (Correct)
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L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL model checking based on negative cycle detection. In Proc. FST TCS, volume 2245 of LNCS, pages 96-107. Springer, 2001. 14
Distribution of Explicit-State LTL Model-Checking - Brim, Barnat (2003) Self-citation (Brim) (Correct)
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Brim, L., I. Cerna, P. Krcal and R. Pelanek, Distributed ltl model checking based on negative cycle detection, in: FSTTCS 2001.
Parallel Breadth-First Search LTL Model-Checking - Jir Barnat Lubos (2003) (1 citation) Self-citation (Brim) (Correct)
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L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL model checking based on negative cycle detection. In R. Hariharan, M. Mukund, and V. Vinay, editors, Proceedings of Foundations of Software Technology and Theoretical Computer Science (FST--TCS'01), volume 2245 of LNCS, pages 96--107. Springer Verlag, 2001.
Unknown - Ya--- Fi Mu (2001) Self-citation (Brim Cern Krcl Pelnek) (Correct)
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L. Brim, I. Cern, P. Krcl, and R. Pelnek. Distributed LTL model checking based on negative cycle detection. Submitted to 21st Foundations of Software Technology and Theoretical Computer Science, 2001.
Distributed Explicit Fair Cycle Detection: Set Based Approach - Cerna, Pelnek (2002) Self-citation (Cerna Pelanek) (Correct)
....parallel computer with a huge amount of memory. Reports by several independent groups ( 33, 28, 17, 4, 3] have confirmed the usefulness of distributed algorithms for the state space generation and reachability analysis. Methods for distributing LTL and CTL model checking have been presented in [1, 2, 8] and [6] respectively. However, until today not much effort has been taken to consider distributed algorithms for fair cycle detection. In our search for an effective distributed algorithm let us first discuss diverse sequential algorithms for fair cycle detection. In explicit algorithms the ....
....procedure visits each state only once. NESTEDBFS visits only states in S and once a state is completely searched by NESTEDBFS it is removed from S. Hence, NESTEDBFS visits each state at most once too. 4 Distributed Algorithm Similar to other works devoted to the distributed model checking [6, 3, 8, 33, 4] we assume the MIMD architecture of a network of workstations, which communicate via message passing (no global information is directly accessible) All workstations execute the same program. One workstation is distinguished as a Manager and is responsible for the initialisation of the ....
[Article contains additional citation context not shown here]
L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL model checking based on negative cycle detection. In Proc. Foundations of Software Technology and Theoretical Computer Science, volume 2245 of LNCS, pages 96--107. Springer, 2001.
Distributed Explicit Fair Cycle Detection: Set Based Approach - Cerna, Pelnek Self-citation (Cern) (Correct)
....computer with a huge amount of memory. Reports by several independent groups ( 33, 28, 17, 4, 3] have con Thetarmed the usefulness of distributed algorithms for the state space generation and reachability analysis. Methods for distributing LTL and CTL model checking have been presented in [1, 2, 8] and [6] respectively. However, until today not much effort has been taken to consider distributed algorithms for fair cycle detection. In our search for an effective distributed algorithm let us Thetarst discuss diverse sequential algorithms for fair cycle detection. In explicit algorithms the ....
....procedure visits each state only once. NESTEDBFS visits only states in S and once a state is completely searched by NESTEDBFS it is removed from S. Hence, NESTEDBFS visits each state at most once too. 4 Distributed Algorithm Similar to other works devoted to the distributed model checking [6, 3, 8, 33, 4] we assume the MIMD architecture of a network of workstations, which communicate via message passing (no global information is directly accessible) All workstations execute the same program. One workstation is distinguished as a Manager and is responsible for the initialisation of the ....
[Article contains additional citation context not shown here]
L. Brim, I. i Cern#a, P. Kric#al, and R. Pel#anek. Distributed LTL model checking based on negative cycle detection. In Proc. Foundations of Software Technology and Theoretical Computer Science, volume 2245 of LNCS, pages 96#107. Springer, 2001.
Distributed Shortest Paths for Directed Graphs.. - Brim.. (2001) Self-citation (Brim Cern) (Correct)
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L. Brim, I. i Cern#, P. Kric#l, and R. Pel#nek. Distributed LTL model checking based on negative cycle detection. Submitted to 21st Foundations of Software Technology and Theoretical Computer Science, 2001.
Property Driven Distribution of Nested DFS - Barnat, Brim, Cerna (2002) (5 citations) Self-citation (Brim Cern) (Correct)
....The algorithm was chosen not only because of its eciency, but also because a distribution of this algorithm seems to be a natural extension of commonly used veri cation tools such as SPIN. The other reason was that we would like to improve our two distributed algorithms for LTL model checking ([2, 5]) Both of them have used partition functions that randomly distribute the state space among the network nodes. The new technique presented in this paper is independent of them, hence, it provides their natural supplementary improvement. A naive approach to the distribution is obvious. The ....
.... type N randomly on network nodes which is possible because the only relevant information for these states is their reachability and it can be analysed e.g. using the algorithm of Lerda and Sisto[10] The computation over components of type P and F can be distributed using algorithms presented in [2, 5]. We intend to implement and experiment other strategies for distribution of the veri cation problem that use additional information gained from the veri ed property. Also, we would like to continue our search for similar improvements achieved through exploring the structure of the modeled ....
L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL Model Checking Based on Negative Cycle Detection. In Ramesh Hariharan, Madhavan Mukund, and V. Vinay, editors, FST TCS 2001, volume 2245 of LNCS, pages 96-107. Springer, 2001.
Property Driven Distribution of Nested DFS - Barnat, Brim, Cerna (2002) (5 citations) Self-citation (Brim Cern) (Correct)
....The algorithm was chosen not only because of its eciency, but also because a distribution of this algorithm seems to be a natural extension of commonly used veri cation tools such as SPIN. The other reason was that we would like to improve our two distributed algorithms for LTL model checking ([2, 5]) Both of them have used partition functions that randomly distribute the state space among the network nodes. The new technique presented in this paper is independent of them, hence, it provides their natural supplementary improvement. 2 A naive approach to the distribution is obvious. The ....
....N randomly on network nodes. This is possible because the only relevant information for these states is their reachability and can be analysed e.g. using the algorithm of Lerda and Sisto[10] The other parts of graph which are of type P and F can be distributed using algorithm presented in [2] or [5] or using the simplest baton algorithm. 9 In the future we intend to implement and experiment other strategies for distribution of the veri cation problem that uses additional information from the veri ed property. Also, we would like to continue our search for similar improvements achieved by ....
L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL Model Checking Based on Negative Cycle Detection. In Ramesh Hariharan, Madhavan Mukund, and V. Vinay, editors, FST TCS 2001, volume 2245 of LNCS, pages 96-107. Springer, 2001.
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L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL modelchecking based on negative cycle detection. In Proceedings of 21st Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'01), Lecture Notes in Computer Science. Springer, Dec. 2001.
Parallel Model Checking for LTL, CTL*, and L ²μ - Leucker, Somla, Weber (2003) (Correct)
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L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL modelchecking based on negative cycle detection. In Proceedings of 21st Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'01), Lecture Notes in Computer Science. Springer, Dec. 2001.
Parallel Model Checking for LTL, CTL*, and L²μ - Leucker, Somla, Weber (Correct)
No context found.
L. Brim, I. Cerna, P. Krcal, and R. Pelanek. Distributed LTL modelchecking based on negative cycle detection. In Proceedings of 21st Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS'01), Lecture Notes in Computer Science. Springer, Dec. 2001.
The Parallel PV Model-Checker - Palmer, Gopalakrishnan (Correct)
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Lubos Brim, Ivana Cerna, Pavel Krcal, and Radek Pelanek. Distributed ltl model checking based on negative cycle detection. In Proceedings of the FSTTCS Conference, 2001. Bangalore, India, December 2001. To appear.
Tools Day - Cerna (2002) (Correct)
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Lubos Brim, Ivana Cerna, Pavel Krcal, and Radek Pelanek. Distributed ltl model checking based on negative cycle detection. In Proceedings of the FSTTCS Conference, 2001. Bangalore, India, December 2001. To appear.
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