GEDLIB: A C++ Library for Graph Edit Distance Computation

David B. Blumenthal, Sébastien Bougleux, Johann Gamper, Luc Brun

Abstract: The graph edit distance (\(\mathrm {GED}\)) is a flexible graph dissimilarity measure widely used within the structural pattern recognition field. In this paper, we present GEDLIB, a C++ library for exactly or approximately computing \(\mathrm {GED}\). Many existing algorithms for \(\mathrm {GED}\) are already implemented in GEDLIB. Moreover, GEDLIB is designed to be easily extensible: for implementing new edit cost functions and \(\mathrm {GED}\) algorithms, it suffices to implement abstract classes contained in the library. For implementing these extensions, the user has access to a wide range of utilities, such as deep neural networks, support vector machines, mixed integer linear programming solvers, a blackbox optimizer, and solvers for the linear sum assignment problem with and without error-correction.