Generation of a Set of Event Logs with Noise
Process mining is a relatively new research area aiming to extract process models from event logs of real systems. A lot of new approaches and algorithms are developed in this ﬁeld. Researches and developers usually have a need to test end evaluate the newly constructed algorithms. In this paper we propose a new approach for generation of event logs. It serves to facilitate the process of evaluation and testing. Presented approach allows to generate event logs, and sets of event logs to support a large scale testing in a more automated manner. Another feature of the approach is a generation of event logs with noise. This feature allows to simulate real-life system execution with inefﬁciencies, drawbacks, and crashes. In this work we also consider other existing approaches. Their forces and weaknesses are shown. The approach presented as well as the corresponding tool can be widely used in the research and development process.