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Model-based verification of event-driven business processes

Authors:

Christian Reinartz,

Andreas Metzger,

Klaus PohlAuthors Info & Claims

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

Pages 1 - 9

https://doi.org/10.1145/2675743.2771826

Published: 24 June 2015 Publication History

Abstract

Event-driven business processes employ event-processing capabilities to analyze internal and external event streams for complex situations that may impact on process execution. An open issue is the verification of such event-driven business processes in order to detect, among others, deadlocks. Individual verification approaches for business processes and event processing networks exist. However, even if the business processes and the event processing networks individually are deadlock-free, deadlocks may arise due to the integration of event processing networks and business processes into event-driven business processes. This paper introduces a verification technique for event-driven business processes. The main aspects of the technique are (1) to formalize business process models and event processing networks as an integrated petri-net, and (2) to perform reachability analyses of the integrated petri-nets to reveal deadlocks. We provide a proof-of-concept realization utilizing petri-net simulators, demonstrate the applicability of the verification technique, and sketch future extensions of the technique.

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Cited By

Metzger AReinartz CPohl K(2018)Incremental Verification of Complex Event Processing Applications for System Monitoring2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA.2018.00055(293-297)Online publication date: Aug-2018
https://doi.org/10.1109/SEAA.2018.00055
Underwood M(2016)Big Data Complex Event Processing for Internet of Things Provenance: Benefits for Audit, Forensics, and SafetyCyber‐Assurance for the Internet of Things10.1002/9781119193784.ch8(209-223)Online publication date: 17-Dec-2016
https://doi.org/10.1002/9781119193784.ch8
(2016)BibliographyCyber‐Assurance for the Internet of Things10.1002/9781119193784.biblio(433-455)Online publication date: 17-Dec-2016
https://doi.org/10.1002/9781119193784.biblio

Index Terms

Model-based verification of event-driven business processes

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Published In

cover image ACM Conferences

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

June 2015

385 pages

ISBN:9781450332866

DOI:10.1145/2675743

General Chairs:
Frank Eliassen
University of Oslo, Norway
,
Roman Vitenberg
University of Oslo, Norway

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 24 June 2015

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Seventh Framework Programme

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DEBS '15

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DEBS '15: The 9th ACM International Conference on Distributed Event-Based Systems

June 29 - July 3, 2015

Oslo, Norway

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Cited By

Metzger AReinartz CPohl K(2018)Incremental Verification of Complex Event Processing Applications for System Monitoring2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA.2018.00055(293-297)Online publication date: Aug-2018
https://doi.org/10.1109/SEAA.2018.00055
Underwood M(2016)Big Data Complex Event Processing for Internet of Things Provenance: Benefits for Audit, Forensics, and SafetyCyber‐Assurance for the Internet of Things10.1002/9781119193784.ch8(209-223)Online publication date: 17-Dec-2016
https://doi.org/10.1002/9781119193784.ch8
(2016)BibliographyCyber‐Assurance for the Internet of Things10.1002/9781119193784.biblio(433-455)Online publication date: 17-Dec-2016
https://doi.org/10.1002/9781119193784.biblio

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