When the first process discovery algorithms were being developed, the question arose whether the result was actually any good. Algorithms, such as Little Thumb and the Alpha Miner were shown to be able to reproduce the model used to generate data, but in a realistic setting, that model would not be available (otherwise, why would you use process mining?) This simple question: “Is my model a good model for this dataset?” sparked an entire research area, known today as conformance checking.