Abstract
Data is the new raw material for business. As regards Business Process Management, this natural resource is contained into a process log in the form of recorded executions of process instances. In this framework, the evaluation of process mining techniques like process discovery and conformance checking demands for solid benchmark suites composed of logs with specific characteristics, which are rarely available in real contexts. Although the creation of the “perfect log” is certainly an unattainable hope, the availability of tools for synthetic log generation could simplify the development and test of novel process mining techniques. In this work, starting from an existing approach based on Abductive Logic Programming, we further report on a tool for synthetic log generation based on this approach, and suggest a practical application of the tool in the field of process engineering.