Introduction

Evaluating process mining algorithms could require the availability of a suite of real-world business processes and their execution logs, which hardly are available.

Process Log Generator is a application capable to generate random business processes, starting from some general "complexity paramenters". PLG is also able to "execute" a given process model in order to generate a process log.

This software is designed to help researchers in the construction of a large set of processes and corresponding execution logs. This software is released with a small library which could help in the programmatical creation of processes.

Main Features

• Random generation and simulation of complex process models;
• Random generation and simulation of complex data objects;
• Detailed tweaking of activities time features;
• Random evolution of a process model, in order to generate a slightly different version of it (to simulate concept drifts);
• Deep control on the generated simulation noise;
• Event stream generation, and, while the stream is running, straightaway switch of the underlying simulated model, to simulate concept drifts;
• Process model import from PLG2 or BPMN XML files (designed with Signavio);
• Models export as BPMN 2.0 XML, BPMN/Petri net Graphviz Dot files, PNML and PLG2.

Screencast Demo

Download

You can read or download the updated Java source code on the project GitHub. Sources of the old releases of PLG are still available on the old GitHub project.

Alternatively, you can download the binary version from the table below:

v2.0.7 (most recent release)

• Release date: 2022-01-30
• Download this release (sources and binary)
• Release notes:

  A couple of bug fixes with icons loading.

Help and Contact

You can find more information on how to use the tool and how to configure it, on the GihHub Wiki pages. You can find all the contact information at the author's webpage.

Citation

Please, cite this work as:

• Andrea Burattin. "PLG2: Multiperspective Process Randomization with Online and Offline Simulations". In Online Proceedings of the BPM Demo Track 2016; Rio de Janeiro, Brasil; September 18, 2016; CEUR-WS.org 2016.

Other relevant publications:

• Andrea Burattin. "PLG2: Multiperspective Processes Randomization and Simulation for Online and Offline Settings". In CoRR abs/1506.08415, Jun. 2015.
• Andrea Burattin and Alessandro Sperduti. "PLG: a Framework for the Generation of Business Process Models and their Execution Logs". In Proceedings of the 6th International Workshop on Business Process Intelligence (BPI 2010); Stevens Institute of Technology; Hoboken, New Jersey, USA; September 13, 2010. 10.1007/978-3-642-20511-8_20.