Symbolic Model Generation for Graph Properties (bibtex)
by , ,
Abstract:
Graphs are ubiquitous in Computer Science. For this reason, in many areas, it is very important to have the means to express and reason about graph properties. In particular, we want to be able to check automatically if a given graph property is satisfiable. Actually, in most application scenarios it is desirable to be able to explore graphs satisfying the graph property if they exist or even to get a complete and compact overview of the graphs satisfying the graph property. We show that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph properties. Graph properties are formulated in a dedicated logic making use of graphs and graph morphisms, which is equivalent to first-order logic on graphs as introduced by Courcelle. Our parallelizable algorithm gradually generates a finite set of so-called symbolic models, where each symbolic model describes a set of finite graphs (i.e., finite models) satisfying the graph property. The set of symbolic models jointly describes all finite models for the graph property (complete) and does not describe any finite graph violating the graph property (sound). Moreover, no symbolic model is already covered by another one (compact). Finally, the algorithm is able to generate from each symbolic model a minimal finite model immediately and allows for an exploration of further finite models. The algorithm is implemented in the new tool AutoGraph.
Reference:
Symbolic Model Generation for Graph Properties (Sven Schneider, Leen Lambers, Fernando Orejas), In Proc. Fundamental Approaches to Software Engineering (FASE'17) (Marieke Huisman, Julia Rubin, eds.), Springer, 2017.
Bibtex Entry:
@InProceedings{SLO17,
AUTHOR = {Schneider, Sven and Lambers, Leen and Orejas, Fernando},
TITLE = {{Symbolic Model Generation for Graph Properties}},
YEAR = {2017},
BOOKTITLE = {Proc. Fundamental Approaches to Software Engineering (FASE'17)},
PAGES = {226-243},
EDITOR = {Huisman, Marieke and Rubin, Julia},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Uppsala, Sweden},
PUBLISHER = {Springer},
URL = {http://link.springer.com/chapter/10.1007/978-3-662-54494-5_13},
ABSTRACT = {Graphs are ubiquitous in Computer Science. For this reason,
in many areas, it is very important to have the means to express and
reason about graph properties. In particular, we want to be able to check
automatically if a given graph property is satisfiable. Actually, in most
application scenarios it is desirable to be able to explore graphs satisfying
the graph property if they exist or even to get a complete and compact
overview of the graphs satisfying the graph property.
We show that the tableau-based reasoning method for graph properties
as introduced by Lambers and Orejas paves the way for a symbolic
model generation algorithm for graph properties. Graph properties are
formulated in a dedicated logic making use of graphs and graph morphisms,
which is equivalent to first-order logic on graphs as introduced
by Courcelle. Our parallelizable algorithm gradually generates a finite
set of so-called symbolic models, where each symbolic model describes a
set of finite graphs (i.e., finite models) satisfying the graph property. The
set of symbolic models jointly describes all finite models for the graph
property (complete) and does not describe any finite graph violating the
graph property (sound). Moreover, no symbolic model is already covered
by another one (compact). Finally, the algorithm is able to generate from
each symbolic model a minimal finite model immediately and allows for
an exploration of further finite models. The algorithm is implemented in
the new tool AutoGraph.}
}
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