In machine learning and genetic programming it is common to train the system using known examples. In GP the set of examples used for training is commonly called the test set. A program's fitness is often based solely upon its performance on the test set. A common performance measure is the number of examples it gets right. Each (approximately) correct answer is known as a hit.
