When a computer system is expensive to use or is not often available, one may want to tune software for it via analytical models that run on more common, less costly machines. In contrast, if the host system is readily available, the attraction of analytical models is far less. One instead employs the actual system, testing and tuning its software empirically. Two examples of code scalability testing illustrate how these approaches differ in objectives and costs, and, how they complement each other in usefulness