Detailed Information on Publication Record
2019
Abstract Dependency Graphs and Their Application to Model Checking
ENEVOLDSEN, Soeren, Kim G. LARSEN and Jiří SRBABasic information
Original name
Abstract Dependency Graphs and Their Application to Model Checking
Authors
ENEVOLDSEN, Soeren (208 Denmark), Kim G. LARSEN (208 Denmark) and Jiří SRBA (203 Czech Republic, guarantor, belonging to the institution)
Edition
The Netherlands, Proceedings of the 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS'19), p. 316-333, 18 pp. 2019
Publisher
Springer
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Netherlands
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
Impact factor
Impact factor: 0.402 in 2005
RIV identification code
RIV/00216224:14330/19:00113640
Organization unit
Faculty of Informatics
ISBN
978-3-030-17461-3
ISSN
UT WoS
000681166500018
Keywords in English
dependency graph; on-the-fly algorithms; verification; model checking
Změněno: 16/5/2022 14:27, Mgr. Michal Petr
Abstract
V originále
Dependency graphs, invented by Liu and Smolka in 1998, are oriented graphs with hyperedges that represent dependencies among the values of the vertices. Numerous model checking problems are reducible to a computation of the minimum fixed-point vertex assignment. Recent works successfully extended the assignments in dependency graphs from the Boolean domain into more general domains in order to speed up the fixed-point computation or to apply the formalism to a more general setting of e.g. weighted logics. All these extensions require separate correctness proofs of the fixed-point algorithm as well as a one-purpose implementation. We suggest the notion of abstract dependency graphs where the vertex assignment is defined over an abstract algebraic structure of Noetherian partial orders with the least element. We show that existing approaches are concrete instances of our general framework and provide an open-source C++ library that implements the abstract algorithm. We demonstrate that the performance of our generic implementation is comparable to, and sometimes even outperforms, dedicated special-purpose algorithms presented in the literature.