Applying graph grammars for the generation of process models and their logs

This work is dedicated to one of the most urgent problems in the field of process mining. Process mining is a technique that offers plenty of methods for the discovery and analysis of business processes based on event logs. However, there is a lack of real process models and event logs, which can be used to verify the methods developed to achieve process mining goals. Hence, there is a need in an instrument that would generate process models and logs, thus allowing verification of the process mining discovery algorithms. This aim can be reached by the creation of a model and log generator. In this paper a possible solution for the creation of such a generator will be proposed. Namely, it is the generation of process models and event logs using the rules of graph grammars on the example of structured workflow nets. The approach proposed is based on the creation of grammar rules to generate a model and an event log, which fits this model. The evaluation of the process discovery algorithms will be available due to the presence of initial models and event logs generated on the basis of these models. The tools used to perform this work are publicly available. This paper is the research-in-progress, which is conducted in frame of master’s thesis in the field of software engineering. Keyword: process mining, discovery algorithms, conformance checking, graph rewriting rules, graph grammar, event logs.