  Services and products are often offered via the execution of processes that
vary according to the context, requirements, or customisation needs. The
analysis of such process variants can highlight differences in the service
outcome or quality, leading to process adjustments and improvement. Research in
the area of process mining has provided several methods for process variants
analysis. However, very few of those account for a statistical significance
analysis of their output. Moreover, those techniques detect differences at the
level of process traces, single activities, or performance. In this paper, we
aim at describing the distinctive behavioural characteristics between variants
expressed in the form of declarative process rules. The contribution to the
research area is two-pronged: the use of declarative rules for the explanation
of the process variants and the statistical significance analysis of the
outcome. We assess the proposed method by comparing its results to the most
recent process variants analysis methods. Our results demonstrate not only that
declarative rules reveal differences at an unprecedented level of
expressiveness, but also that our method outperforms the state of the art in
terms of execution time.
