  Process mining methods allow analysts to use logs of historical executions of
business processes in order to gain knowledge about the actual behavior of
these processes. One of the most widely studied process mining operations is
automated process discovery. An event log is taken as input by an automated
process discovery method and produces a business process model as output that
captures the control-flow relations between tasks that are described by the
event log. In this setting, this paper provides a systematic comparative
evaluation of existing implementations of automated process discovery methods
with domain experts by using a real-life event log extracted from an
international software engineering company and four quality metrics. The
evaluation results highlight gaps and unexplored trade-offs in the field and
allow researchers to improve the lacks in the automated process discovery
methods in terms of usability of process discovery techniques in industry.
