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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Ivan Shugurov
Program for Generation of Artificial Event Logs for BPMN 2.0 Process Models
Software Engineering
(Bachelor’s programme)
10
2016
The number of new methods for constructing process models from the history of process executions grows steadily. Representational bias (the class of models considered) plays an important role in process discovery: expressiveness of a modeling language delimits process extracting approaches. During the last two years several techniques for mining high-level process models in terms of BPMN (Business Process Model and Notation) 2.0 were suggested. Nevertheless, due to the high expressive potential of BPMN 2.0 there is a shortage of methods to discover many of high-level BPMN 2.0 modeling constructs. Moreover, a lack of suitable event logs makes development of such discovery methods impossible.

This work suggests approaches for generating event logs for BPMN 2.0 process models. All these approaches were implemented as a part of a program, which extends ProM (Process Mining Framework). The program supports BPMN elements which are frequently employed in scientific and industrial practice. The chosen elements allow for modeling of all perspectives of any business process control flow perspective, resource perspective, and data flow perspective. As a result, the program is capable of the generation of artificial event logs based on a wide range of BPMN models including those with high-level constructs.

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