RL-align performs conformance checking aligning log traces with a PM Petri net. It uses relaxation labeling (RL) constraint satisfaction algorithm to perform the alignment.
Obtained alignments may be suboptimal, but the computation time is linear with the trace length, offering computation times about two orders of magnitude faster than other state-of-the-art methods.
This software is further described in the following papers:
Version 1.0 (tag v1.0 in gitHub)
Padró, L., Carmona, J., 2019.
Approximate computation of alignments of business processes through relaxation labelling,
in: Business Process Management - 17th International Conference, BPM 2019, pp. 250–267.
Vienna, Austria, September 1-6, 2019
Version 3 (tag v3 in gitHub)
[Submitted]
- Alignments are now suboptimal instead of approximate (i.e. a Fitting alignment is always produced, even if it is not the optimal)
- Replaced computation of Behavioural Profiles using
jbptwith our own C++ faster code.
RL-align is distributed under an Affero GPL license.
The code includes the pugixml parser which is distributed under MIT license
The binary for punf Petri Net Unfolder is also included, dowloaded from [Victor Khomenko's web page]
To run RL-align you'll need a standard linux box with g++5 or later.
Go to folder src and compile RL-align components:
cd src
make
Now you are ready to use the software.
Folder data contains data files to test the aligner:
originals: Original pnml models.logs: XES trace log files.alignments: Alignments produced by other State-of-the-art alignment methods
You can add you own models and traces, as long as the filenames are consistent, and they are in the right folders.
Some preprocessing is required on your target models before runnig the aligner. The preprocess consists of computing the unfoldings, the shortest paths between model nodes, and the Behavioral Profiles.
To execute the process run:
bin/preprocess-data.sh 2>err.log
(redirecting stderr is recommended since punf is very verbose)
This preprocess will process each model in data/originals folder and for each of them, it will create in data/unfoldings the following files: .bp.pnml (unfolding), .bp (behavioral profiles) and .path (shortest paths files).
This is required only once. After that you can run the aligner as many times as needed.
The aligner can be run providing a configuration file and a list of models to be aligned.
bin/execute.sh configfile models
On example configuration file is provided: config.15.5.-100.-150.-300.cfg, which produces alignment lower costs on the used tuning dataset.
The model file must be in data/unfoldings and have extension .bp.pnml. Behavioural profiles and shortest paths should be already precomputed and reside in the same folder. The execute.sh script expects the trace files to be in data/logs and have the same name than the model, but with extension .xes.
E.g., to align one model with its corresponding log:
bin/execute.sh config/config.15.5.-100.-150.-300.cfg data/unfoldings/M1.bp.pnml
You can also align several models (quotes are important if you do this):
bin/execute.sh config/config.15.5.-100.-150.-300.cfg "data/unfoldings/M1.bp.pnml data/unfoldings/ML3.bp.pnml data/unfoldings/BPIC2017.bp.pnml"
This will leave the results in a folder named data/results/output.15.5.-100.-150.-300 (or whatever was the name of the config file)
For each aligned model, a file will be created containing all aligned traces.
There are two scripts you can use to evaluate the alignments:
- The script
eval-relax.shwill evaluate results of relaxation labelling aligner
E.g.
cat data/results/output.15.5.-100.-150.-300/M1.out | bin/eval-relax.sh
You can also compute aggregated results (i.e. to compute microaverage costs and total used CPU time across several models)
cat results/output.15.5.-100.-150.-300/M[0-9]*.out | bin/eval-relax.sh
- The script
eval-prom.shwill evaluate results of aligners in ProM environment, when saved as CSV.
E.g.:
cat data/alignments/ProM-Astar/M1.csv | bin/eval-prom