Group testing is an indispensable tool for laboratories when testing high volumes of clinical specimens for infectious diseases. An important decision that needs to be made prior to its implementation involves determining what group sizes to use. In best practice, an objective function is chosen and then minimized to determine an optimal set of these group sizes, known as the optimal testing configuration (OTC). There are a few options for objective functions, and they differ based on how the expected number of tests, assay characteristics, and laboratory constraints are taken into account. These varied options have led to a recent controversy in the group testing literature regarding which objective function is best. In our presentation, we examine the most commonly proposed objective functions. We show that this controversy may be "much ado about nothing" because the OTCs, group sizes, and corresponding results (e.g., expected number of tests, accuracy measures) from using the two most commonly proposed objective functions are largely the same for standard testing algorithms in a wide variety of situations.