Graphs are a widely used data structure to represent relationships between entities, where vertices correspond to objects and edges describe the connections between them. Examples range from chemical structures, where atoms are connected by bonds, to social networks, where users are linked by friendships. In this work, we focus on undirected, vertex-labeled graphs, a common representation in many domains where entities and their relationships need to be modeled. The main problem addressed is the subgraph isomorphism task, which aims to identify occurrences of a smaller graph pattern within a much larger graph dataset. This problem is known to be computationally challenging and has applications across diverse areas such as network analysis, bioinformatics, and cheminformatics.