TY - JOUR

T1 - Testing Properties of Directed Graphs

T2 - Acyclicity and Connectivity

AU - Bender, Michael A.

AU - Ron, Dana

PY - 2002/3

Y1 - 2002/3

N2 - This article initiates the study of testing properties of directed graphs. In particular, the article considers the most basic property of directed graphs - acyclicity. Because the choice of representation affects the choice of algorithm, the two main representations of graphs are studied. For the adjacency-matrix representation, most appropriate for dense graphs, a testing algorithm is developed that requires query and time complexity of (Õ(1/∈2), where ∈ is a distance parameter independent of the size of the graph. The algorithm, which can probe the adjacency matrix of the graph, accepts every graph that is acyclic, and rejects, with probability at least 2/3, every graph whose adjacency matrix should be modified in at least ∈ fraction of its entries so that it becomes acyclic. For the incidence list representation, most appropriate for sparse graphs, an Ω(|V| 1/3) lower bound is proved on the number of queries and the time required for testing, where V is the set of vertices in the graph. Along with acyclicity, this article considers the property of strong connectivity. Contrasting upper and lower bounds are proved for the incidence list representation, In particular, if the testing algorithm can query on both incoming and outgoing edges at each vertex, then it is possible to test strong connectivity in Õ(1/∈) time and query complexity. On the other hand, if the testing algorithm only has access to outgoing edges, then Ω(√N) queries are required to test for strong connectivity.

AB - This article initiates the study of testing properties of directed graphs. In particular, the article considers the most basic property of directed graphs - acyclicity. Because the choice of representation affects the choice of algorithm, the two main representations of graphs are studied. For the adjacency-matrix representation, most appropriate for dense graphs, a testing algorithm is developed that requires query and time complexity of (Õ(1/∈2), where ∈ is a distance parameter independent of the size of the graph. The algorithm, which can probe the adjacency matrix of the graph, accepts every graph that is acyclic, and rejects, with probability at least 2/3, every graph whose adjacency matrix should be modified in at least ∈ fraction of its entries so that it becomes acyclic. For the incidence list representation, most appropriate for sparse graphs, an Ω(|V| 1/3) lower bound is proved on the number of queries and the time required for testing, where V is the set of vertices in the graph. Along with acyclicity, this article considers the property of strong connectivity. Contrasting upper and lower bounds are proved for the incidence list representation, In particular, if the testing algorithm can query on both incoming and outgoing edges at each vertex, then it is possible to test strong connectivity in Õ(1/∈) time and query complexity. On the other hand, if the testing algorithm only has access to outgoing edges, then Ω(√N) queries are required to test for strong connectivity.

UR - http://www.scopus.com/inward/record.url?scp=0036110133&partnerID=8YFLogxK

U2 - 10.1002/rsa.10023

DO - 10.1002/rsa.10023

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AN - SCOPUS:0036110133

SN - 1042-9832

VL - 20

SP - 184

EP - 205

JO - Random Structures and Algorithms

JF - Random Structures and Algorithms

IS - 2

ER -