Abstract
To carry on controlled experiments in process mining, it is necessary to generate event logs with specific characteristics. This has led to the development of log generation techniques in which a process model is simulated to generate an event log that is both compliant with the process model and also has certain user-defined properties (e.g., a certain number of traces, traces with certain lengths, etc.). Such techniques are available for a variety of modeling languages, both procedural and declarative. However, they are limited to simulating a single (procedural or declarative) process model at a time and do not allow simulating concurrent executions of multiple separate, but interacting, processes. In this paper, we introduce a log generation approach that takes multiple (procedural and declarative) process models (i.e., a Hybrid Business Process Representation) as input and produces an event log matching the concurrent execution of these models on the same case instances. We discuss the details of our approach and evaluate its implementation.