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https://doi.org/10.1109/ccc.20...
Article . 2007 . Peer-reviewed
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Article . 2007
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Testing Properties of Constraint-Graphs

Authors: Shirley Halevy; Oded Lachish; Ilan Newman; Dekel Tsur;

Testing Properties of Constraint-Graphs

Abstract

We study a model of graph related formulae that we call the constraint-graph model. A constraint-graph is a labeled multi-graph (a graph where loops and parallel edges are allowed), where each edge e is labeled by a distinct Boolean variable and every vertex is associated with a Boolean function over the variables that label its adjacent edges. A Boolean assignment to the variables satisfies the constraint graph if it satisfies every vertex function. We associate with a constraint-graph G the property that consists of all assignments satisfying G, denoted SAT(G). We show that the above model is quite general. That is, for every property of strings P there exists a property of constraint-graphs PG such that P is testable using q queries if and only if PG is thus testable. In addition, we present a large family of constraint-graphs for which SAT(G) is testable with constant number of queries. As an implication of this, we infer the testability of some edge coloring problems (e.g. the property of two coloring of the edges in which every node is adjacent to at least one vertex of each color). Another implication is that every property of Boolean strings that can be represented by a read-twice CNF formula is testable. We note that this is the best possible in terms of the number of occurrences of every variable in a formula.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Top 10%