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Pavel Simecek

dblp:66/1775 · DBLP profile ↗
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7ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 7Theory of computation · 3

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
4 papers
Automated reasoning and model checking · 62% Algorithms and data structures · 17% Distributed computing theory · 15%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Automated reasoning and model checking › model checking › temporal logic model checking
LTL model checking
0.222009
Cluster-Based I/O-Efficient LTL Model Checking · ASE 2009
Semi-external LTL Model Checking · CAV 2008
Automated reasoning and model checking
model checking
0.112008
Semi-external LTL Model Checking · CAV 2008
Distributed computing theory
distributed verification
0.112006
DiVinE - A Tool for Distributed Verification · CAV 2006
High-performance computing
cluster computing
0.012009
Cluster-Based I/O-Efficient LTL Model Checking · ASE 2009
Computational complexity
space complexity
0.012007
I/O Efficient Accepting Cycle Detection · CAV 2007

Methods — techniques the papers use, named apart from their topics

i/o-efficient algorithms · 0.1
YearPublicationVenuePosition
2011 Flash memory efficient LTL model checking
Stefan Edelkamp, Damian Sulewski, Jiri Barnat, Lubos Brim, Pavel Simecek
Sci. Comput. Program.5
2009 Cluster-Based I/O-Efficient LTL Model Checking
abstract
I/O-efficient algorithms take the advantage of large capacities of external memories to verify huge state spaces even on a single machine with low-capacity RAM. On the other hand, parallel algorithms are used to accelerate the computation and their usage may significantly increase the amount of available RAM memory if clusters of computers are involved. Since both the large amount of memory and high speed computation are desired in verification of large-scale industrial systems, extending I/O-efficient model checking to work over a network of computers can bring substantial benefits. In this paper we propose an explicit state cluster-based I/O efficient LTL model checking algorithm that is capable to verify systems with approximately $10^{10}$ states within hours.
Jiri Barnat, Lubos Brim, Pavel Simecek
ASE3
2008 Semi-external LTL Model Checking
Stefan Edelkamp, Peter Sanders 0001, Pavel Simecek
CAV3
2008 Can Flash Memory Help in Model Checking?
Jiri Barnat, Lubos Brim, Stefan Edelkamp, Damian Sulewski, Pavel Simecek
FMICS5
2008 Revisiting Resistance Speeds Up I/O-Efficient LTL Model Checking
Jiri Barnat, Lubos Brim, Pavel Simecek
TACAS3
2007 I/O Efficient Accepting Cycle Detection
Jiri Barnat, Lubos Brim, Pavel Simecek
CAV3
2006 DiVinE - A Tool for Distributed Verification
Jiri Barnat, Lubos Brim, Ivana Cerná, Pavel Moravec 0002, Petr Rockai, Pavel Simecek
CAV6