Efficient Implementation of Color Coding Algorithm for Subgraph Isomorphism Problem

TL;DR

This paper presents an efficient implementation of the color coding algorithm for the subgraph isomorphism problem, reducing memory usage and enabling the handling of larger pattern graphs, while also enumerating all solutions.

Contribution

It introduces a memory-efficient implementation of the color coding algorithm that can handle larger pattern graphs and enumerate all subgraphs, surpassing previous limitations.

Findings

Outperforms existing solvers in handling larger pattern graphs.

Successfully enumerates all subgraphs isomorphic to the pattern.

Reduces memory requirements significantly compared to traditional implementations.

Abstract

We consider the subgraph isomorphism problem where, given two graphs G (source graph) and F (pattern graph), one is to decide whether there is a (not necessarily induced) subgraph of G isomorphic to F. While many practical heuristic algorithms have been developed for the problem, as pointed out by McCreesh et al. [JAIR 2018], for each of them there are rather small instances which they cannot cope. Therefore, developing an alternative approach that could possibly cope with these hard instances would be of interest. A seminal paper by Alon, Yuster and Zwick [J. ACM 1995] introduced the color coding approach to solve the problem, where the main part is a dynamic programming over color subsets and partial mappings. As with many exponential-time dynamic programming algorithms, the memory requirements constitute the main limiting factor for its usage. Because these requirements grow exponentially with the treewidth of the pattern graph, all existing implementations based on the color coding principle restrict themselves to specific pattern graphs, e.g., paths or trees. In contrast, we provide an efficient implementation of the algorithm significantly reducing its memory requirements so that it can be used for pattern graphs of larger treewidth. Moreover, our implementation not only decides the existence of an isomorphic subgraph, but it also enumerates all such subgraphs (or given number of them). We provide an extensive experimental comparison of our implementation to other available solvers for the problem.