Considering rate constants as indeterminates, the concept of unconditional binomiality has been introduced in a recent work and based on linear algebra, an algorithm with polynomial time complexity upper bound on the number of species and reactions has been proposed for reversible chemical reaction networks. Later on, the authors used a modified version of species-reaction graphs and presented an algorithm which performs by adding and deleting edges and changing the labels of the edges in order to test unconditional binomiality. This package includes the implementation of both the graph theoretical algorithm as well as the linear algebra one in Maple, and experiments on biochemical models. Our experiments show that the performance of the graph theoretical approach is similar to or better than the linear algebra approach, while it is drastically faster than Groebner basis and quantifier elimination methods.