The Walsh-Hadamard Transform is a fundamental tool to characterize several cryptographic properties of Boolean functions f:Fn2→F2. It is well-known that this transform can be efficiently computed in O(n2n) steps by using the Fast Walsh Transform (FWT) algorithm, while the naive implementation requires O(22n) steps. In this talk, we investigate a new approach to compute the Walsh-Hadamard transform. The main data structure underlying this method is a binomial tree, where the path back to the root of each node represents a Walsh-Hadamard coefficient, and inductively defines the related scalar product. We show that the Walsh-Hadamard transform is obtained by visiting such a binomial tree, and consider both a depth-first and a breadth-first search strategy to perform this task. Although the resulting algorithms yield the same O(22n) time complexity of the naive Walsh-Hadamard transform, we experimentally observe that they are faster in practice. We then show how to adapt the BFS-based algorithm to check a Boolean function’s correlation immunity order by requiring only its support as an input. Interestingly, this modified algorithm gives an efficient way to check whether a binary matrix of a large number of columns is an orthogonal array. Such a task cannot be practically accomplished with the Fast Walsh-Hadamard Transform procedure, due to the amount of memory required to hold the truth table of the associated Boolean function.