plg

A Business Processes and Logs Generator

https://github.com/delas/plg

Science Score: 41.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.8%) to scientific vocabulary

Keywords

bpm bpmn java petrinet plg processmining simulation
Last synced: 4 months ago · JSON representation ·

Repository

A Business Processes and Logs Generator

Basic Info
Statistics
  • Stars: 32
  • Watchers: 10
  • Forks: 9
  • Open Issues: 5
  • Releases: 7
Topics
bpm bpmn java petrinet plg processmining simulation
Created almost 11 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Citation

README.md

Processes and Logs Generator

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.

More information at the project home page http://plg.processmining.it/.

Attention: this repository is a complete rewriting of the project already available at: https://github.com/delas/plg-old.

Untitled

Main features

  • Random process generation, with different complexity parameters
  • Random process evolution (to generate slight variations of existing processes)
  • Configuration of time for activities duration and time between activities (via Python scripts)
  • Generation of static/dynamic data objects for multi-perspective event log generation (via Python scripts)
  • Import of process from
    • PLG file format
    • BPMN files (generated from SAP Signavio)
  • Export of generated processes as
    • PLG file format
    • BPMN 2.0 XML file
    • BPMN as Graphviz Dot file
    • Petri net as Graphviz Dot file
    • Petri net as LoLA file
    • Petri net as PNML file
    • Petri net as TPN file
  • Generation of an event log with any number of traces
  • Fine-tuned configuration of noise parameters for event log generation
  • Export of the generated event log as
    • XES file (both compressed as .xes.gz and not compressed as .xes)
    • MXML file (both compressed as .mxml.gz and not compressed as .mxml)
  • Generation of an infinite stream of events
  • Event streams generated as MQTT-XES format (cf. https://www.beamline.cloud/mqtt-xes/)
  • Ability to dynamically switch the process generting the events (to simulate concept drift in streams)
  • Generation of noise into the stream

Help

  • Visit the Wiki for all information. Useful quick documentation:

Libraries

PLG makes use of the following libraries: * libPlg: library for processes and event generation * libPlgStream: library for stream generation * libPlgVisualizer: library for process visualization

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.

Owner

  • Name: Andrea Burattin
  • Login: delas
  • Kind: user

Citation (CITATION.md)

## Citation

Please, cite this work as:
* Andrea Burattin. "[PLG2: Multiperspective Process Randomization with Online and Offline Simulations](https://andrea.burattin.net/publications/2016-bpm-demo)". 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](http://arxiv.org/abs/1506.08415)". 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](http://andrea.burattin.net/publications/2010-bpi)". 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](http://dx.doi.org/10.1007/978-3-642-20511-8_20).

GitHub Events

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Dependencies

plg/pom.xml maven
  • com.github.delas:libPlg 0.0.10
  • com.github.delas:libPlgStream 0.0.2
  • com.github.delas:libPlgVisualizer 0.0.3
  • org.apache.commons:commons-compress 1.21
  • org.apache.httpcomponents:httpclient 4.5.14
  • org.apache.httpcomponents:httpcore 4.4.16
  • org.apache.maven:maven-model-builder 3.9.4
  • org.fife.ui:rsyntaxtextarea 2.0.4.1
  • org.ocpsoft.prettytime:prettytime 5.0.7.Final