Conformance checking
Conformance checking is the formal process-mining technique of comparing an event log to a reference process model and producing fitness, precision, generalisation, and simplicity scores. The output quantifies how well the model represents what's actually happening, and where the divergences concentrate.
Conformance is one of the four core process mining activities (discovery, conformance, enhancement, operational support). The fitness score (0-1) measures how much of the log the model can replay; low fitness means the model misses real behaviour. The precision score measures how much the model allows that the log never shows; low precision means the model is too permissive. The trade-off matters because models that score 1.0 on both for any non-trivial log are usually overfit. The pragmatic target: fitness above 0.85, precision above 0.7, and explanations for the major non-fitting variants.