This tool aligns log traces for Business Process Mining using Automated Planning techniques.
This is the output of the cli java -jar app/build/libs/app-0.0.1.jar --help
:
Usage: TraceAligner [-hqV] [-e=encoding] -f=FORMULAS_FILE
-l=LOG_FILE [-o=OUT] LDLf
TraceAligner aligns log trace using Automated Planning techniques.
LDLf If using LDLf formulas.
Default: false
-q, --quiet Quite mode.
-h, --help Show this help message and exit.
-V, --version Print version information and exit.
-l, --log=LOG_FILE Path to the log file.
-f, --formulas=FORMULAS_FILE
Path to the formulas file.
-e, --encoding=encoding The PDDL encoding type.
0: General
1: General with Conjunctive Goals
2: General with Shared States
3: General with Conjunctive Goals and Shared States
4: Strips with Conjunctive Goals
Default: 0
-o, --output=OUT Path to the output folder.
Default: ./output/
We use the Java JDK 1.8
We use Gradle as a build tool. Please check the official website to download it for your platform.
The project depends on the following libraries:
- OpenXES: to handle XES logs;
- Lydia: for the translation of LTLf/LDLf formulas to DFA.
OpenXES is already included in this repository within the third_party
folder.
Instead, to install Lydia, please refer to its official repository.
To build from source, clone the repository:
git clone https://github.com/whitemech/trace-alignment.git
To build and run tests:
./gradlew build
To install:
./gradlew install
Afterwards, to run the program:
java -jar app/build/libs/app-0.0.1.jar
An Apptainer image is available for TraceAligner.
To build the image, run:
apptainer build tracealigner.sif tracealigner.def
Then, you can run TraceAligner with:
./tracealigner.sif --help
This software is released under the MIT License.
Copyright (c) 2021-2023 WhiteMech
If you use TraceAligner in your research, please consider citing the following paper:
@article{si2023dfmmp,
title = {A Tool for Declarative Trace Alignment via Automated Planning},
author = {Giuseppe {De Giacomo} and Francesco Fuggitti and Fabrizio Maria Maggi and Andrea Marrella and Fabio Patrizi},
journal = {Software Impacts},
volume = {16},
pages = {100505},
year = {2023},
issn = {2665-9638},
doi = {https://doi.org/10.1016/j.simpa.2023.100505},
}
This work has been partially funded by the ERC Advanced Grant "WhiteMech" (No. 834228) and by the TAILOR research network (No. 952215), the PRIN project RIPER (No. 20203FFYLK), and the JPMorgan AI Faculty Research Award "Resilience-based Generalized Planning and Strategic Reasoning".