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| Main Authors: | , , , , , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.15470077 |
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Table of Contents:
- <p>This contains the supplementary materials for the paper "Efficient Conformance Checking of Rich Data-Aware Declare Specifications", accepted for publication at BPM 2025. The research focuses on overcoming the limitations of existing conformance checking methods for declarative process models, which are either restricted to control-flow specifications or support only basic data types and comparisons. By leveraging a combination of A* search and SMT (Satisfiability Modulo Theories) solving, the authors develop a novel algorithm that efficiently computes optimal alignments in the presence of general data types and complex data conditions.</p> <p dir="auto">This includes:</p> <ul> <li><strong>Source Code (dada-sources.tar.gz)</strong>: The implementation of the proposed algorithm for efficient conformance checking.</li> <li><strong>Executable (dada.jar)</strong>: An executable version of the tool, allowing users to apply the approach to their own datasets.</li> <li><strong>Dataset (bergami2021-dataset.tar.gz)</strong>: The experimental dataset used to evaluate the performance of the approach. Retrieved from Bergami, G., Maggi, F.M., Marrella, A., Montali, M.: Aligning data-aware declarative process models and event logs. In: Proc. 19th BPM. LNCS, vol. 12875, pp. 235–251 (2021).</li> <li><strong>Raw Results (dada-raw-results-comparison.csv.gz and dada-raw-results-correlation.csv.gz)</strong>: The raw results from the experiments provide insights into the efficiency and effectiveness of the method.</li> </ul>