Titel
Verifying compliance in process choreographies: Foundations, algorithms, and implementation
Autor*in
David Knuplesch
Alphaquest GmbH
... show all
Abstract
The current push towards interoperability drives companies to collaborate through process choreographies. At the same time, they face a jungle of continuously changing regulations, e.g., due to the pandemic and developments such as the BREXIT, which strongly affect cross-organizational collaborations. Think of, for example, supply chains spanning several countries with different and maybe even conflicting COVID19 traveling restrictions. Hence, providing automatic compliance verification in process choreographies is crucial for any cross-organizational business process. A particular challenge concerns the restricted visibility of the partner processes at the presence of global compliance rules (GCR), i.e., rules that span across the process of several partners. This work deals with the question how to verify global compliance if affected tasks are not fully visible. Our idea is to decompose GCRs into so called assertions that can be checked by each affected partner whereby the decomposition is both correct and lossless. The algorithm exploits transitivity properties of the underlying rule specification, and its correctness and complexity are proven, considering advanced aspects such as loops. The algorithm is implemented in a proof-of-concept prototype, including a model checker for verifying compliance. The applicability of the approach is further demonstrated on a real-world manufacturing use case.
Stichwort
Distributed business processesBusiness rulesCompliance managementProcess choreographyBusiness process complianceGlobal compliance rulesRule decomposition
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
phaidra.univie.ac.at/o:1623908
Erschienen in
Titel
Information Systems
Band
108
ISSN
0306-4379
Erscheinungsdatum
2022
Publication
Elsevier BV
Fördergeber
Europäische Union (alle Programme) — 826078
Erscheinungsdatum
2022
Zugänglichkeit
Rechte
Rechteangabe
© 2022 The Author(s)
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