Source code and results investigating stochastic process quality dimensions in process mining. It includes implementations of a number of exploratory conformance measures for stochastic process models in the form of Generalized Stochastic Petri Nets.
This also includes a genetic algorithm for mining stochastic process models, called the Stochastic Evolutionary Tree Miner (SETM).
The main paper describing these experiments is: Burke, Adam T., Sander J. J. Leemans, Moe T. Wynn, Wil M. P. van der Aalst, and Arthur H. M. ter Hofstede. 2024. “A Chance for Models to Show Their Quality: Stochastic Process Model-Log Dimensions.” Information Systems 124: 102382. doi:10.1016/j.is.2024.102382.
Checkout prom-helpers and prob-process-tree
In prob-process-tree, ./gradlew test ; ./gradlew publishToMavenLocal
In prom-helpers, ./gradlew test ; ./gradlew publishToMavenLocal
In spd_dim, ./gradlew test
Statistical analysis and visualization code is in scripts.
Experiments are run with ExperimentRunner. It depends on a configuration property file, with examples files in config.
A standalone command line interface to SETM is in SETMCommandLine.
The class SETMReporter extracts experimental data from XML mrun_* files to pipe-separated files for import into R or other tools.
Measurements and paradigm models are in results/ and models/ respectively.
This project is licensed under the Lesser GNU Public License (LGPL). The source code extends (and forks) the ProM EvolutionaryTreeMiner by J.C.A.M. Buijs (which is LGPL).