Concise and reliable graph-theoretic analysis of complex networks today is a cumbersome task, consisting essentially of the adaptation of intricate libraries for each specific problem instance. The growing number of complex metrics that have been proposed in the last years, which mainly gain significance due to the increasing computational capabilities at hand, have led to important new insights in the field. However, they have solely been implemented as single algorithms, each specialized for the purpose of calculating exactly the targeted metric for a selected type of network graph. A comprehensive, extensible tool for the concise evaluation of graphs is currently not available. For this purpose we introduce the Graph-Theoretic Network Analyzer (GTNA), an efficient, Java-based toolkit for the comprehensive analysis of complex network graphs. GTNA, while already including the main metrics that are used to analyze the complex networks in computer science today, is simple to extend through a well defined plugin interface for metrics, network descriptions and network generator models. Throughout the paper we present the design and simple extensibility of GTNA, as well as the network models and metrics that are already implemented and give examples of its scalability and performance.
['Benjamin Schiller', 'Dirk Bradler', 'Immanuel Schweizer', 'Max Mühlhäuser', 'Thorsten Strufe']
GTNA: a framework for the graph-theoretic network analysis