  Process models are used by human analysts to model and analyse behaviour, and
by machines to verify properties such as soundness, liveness or other
reachability properties, and to compare their expressed behaviour with recorded
behaviour within business processes of organisations. For both human and
machine use, small models are preferable over large and complex models: for
ease of human understanding and to reduce the time spent by machines in state
space explorations. Reduction rules that preserve the behaviour of models have
been defined for Petri nets, however in this paper we show that a subclass of
Petri nets returned by process discovery techniques, that is, block-structured
workflow nets, can be further reduced by considering their block structure in
process trees. We revisit an existing set of reduction rules for process trees
and show that the rules are correct, terminating, confluent and complete, and
for which classes of process trees they are and are not complete. In a
real-life experiment, we show that these rules can reduce process models
discovered from real-life event logs further compared with rules that consider
only Petri net structures.
