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201690 https://hdl.handle.net/2286/R.2.N.201690 http://rightsstatements.org/vocab/InC/1.0/ http://creativecommons.org/licenses/by-nc-sa/4.0 2025-05 24 pages Bickley, Cameron Bazzi, Rida Richa, Andrea Barrett, The Honors College After decades of research, efficient subgraph isomorphism remains a central challenge in graph theory, with important implications for fields such as computer vision, bioinformatics, and social networks. While older solvers relied upon low-overhead search with local filtering, state-of-the-art approaches trade a higher memory and time overhead for a more sophisticated global filtering. This tradeoff allows newer solutions to solve many of the hardest benchmark instances within a set timeout limit, but we conjecture that for some applications a faster solver with a higher timeout rate may be a better choice. We introduce a solver which significantly improves upon the older low-overhead approach through the inclusion of rich local information from the input graphs. When compared against state-of-the-art solutions, we observe that our solver is still less effective on the hardest benchmarks, but significantly outperforms on easier cases. Algorithms Graph Theory Search Problems Local Heuristics for the Subgraph Isomorphism Problem