Soundness Correction of Data Petri Nets

Fuente: arXiv
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Autores principales: Suvorov, Nikolai M., Lomazova, Irina A., Rivkin, Andrey
Formato: Preprint
Publicado: 2024
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author Suvorov, Nikolai M.
Lomazova, Irina A.
Rivkin, Andrey
author_facet Suvorov, Nikolai M.
Lomazova, Irina A.
Rivkin, Andrey
contents A process model is called sound if it always terminates properly and each model activity can occur in a process instance. Conducting soundness verification right after process design allows one to detect and eliminate design errors in a process to be implemented. The process of eliminating such errors is called soundness repair. In many repair scenarios, the resulting model should retain only the correct behavior of the source model, especially if a model is created manually. In this paper, we consider this type of soundness repair applied to data-aware process models represented as data Petri nets (DPNs). Specifically, we investigate the capabilities to repair soundness of DPNs by restricting the transition guards and propose a new repair algorithm that follows this approach. A distinctive feature of the algorithm is the absence of a requirement for an input DPN to have a sound control flow. The algorithm is implemented and results of the preliminary evaluation demonstrate its applicability to process models of moderate sizes.
format Preprint
id arxiv_https___arxiv_org_abs_2410_21188
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Soundness Correction of Data Petri Nets
Suvorov, Nikolai M.
Lomazova, Irina A.
Rivkin, Andrey
Logic in Computer Science
A process model is called sound if it always terminates properly and each model activity can occur in a process instance. Conducting soundness verification right after process design allows one to detect and eliminate design errors in a process to be implemented. The process of eliminating such errors is called soundness repair. In many repair scenarios, the resulting model should retain only the correct behavior of the source model, especially if a model is created manually. In this paper, we consider this type of soundness repair applied to data-aware process models represented as data Petri nets (DPNs). Specifically, we investigate the capabilities to repair soundness of DPNs by restricting the transition guards and propose a new repair algorithm that follows this approach. A distinctive feature of the algorithm is the absence of a requirement for an input DPN to have a sound control flow. The algorithm is implemented and results of the preliminary evaluation demonstrate its applicability to process models of moderate sizes.
title Soundness Correction of Data Petri Nets
topic Logic in Computer Science
url https://arxiv.org/abs/2410.21188