D 2019

Abstract Dependency Graphs and Their Application to Model Checking

ENEVOLDSEN, Soeren, Kim G. LARSEN and Jiří SRBA

Basic 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.