Data Science is one of the most active fields of research, over past decades, the number of mathematicians, statisticians, computer scientists and engineers working on the different subareas of data science has grown tremendously. Since we live in a digital era, our devices are storing and processing data all the time, then fast algorithms are useful to save time, money and energy consumption. Group Testing problem arises in numerous areas of technology such as machine learning, coding theory, medicine and signal processing due to its low complexity. The main goal is to recover a set of K defective items from a total set of n items by performing the minimum quantity of tests as possible. Each test is related to a chosen subset of n. The test returns positive if there is at least one defective item in the subset tested and negative otherwise. In this work we present the algorithm SAFFRON (Sparse GrAph codes Framework for GROup TestiNg) proposed by the authors Kangwook Lee, Ramtin Pedarsani and Kannan Ranchamdran. We discuss the sophisticated mathematics used, generalizations, we present the theoretical guarantees of the algorithm and we also support our work with numerical simulations as well.