GitHub repository recommendations have been widely developed with inspiration from the Closely reLated ApplicatioNs (Zhang et al., 2017) algorithm. Repopal leverages software tags instead of the API usage patterns used by CLAN. This project will seek to understand the advantages and disadvantages of RepoPal in finding a GitHub repository recommendation based on three heuristics. Analysis regarding the quality of the recommendation, the time taken to gather this information and expectations moving forward using this algorithm will be done. By extension, details regarding algorithm design and construction, as well as it is constraints will be outlined.