Zoom and Enhance: Action Refinement via Subprocesses in Timed Declarative Processes

Håkon Normann, Søren Debois*, Tijs Slaats, Thomas T. Hildebrandt

*Corresponding author af dette arbejde

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

2 Citationer (Scopus)

Abstract

This paper addresses the open technical problems of evolving executable, event-based process models by refinement, that is, by iteratively expanding a model until it has the required level of detail. Such iterative development is helpful because of the expectation that the next-step model is semantically compatible with the previous one, only with more detail. We provide in this paper a formal notion of refinement of single atomic actions (events) into entire subprocesses, and a theoretical framework for providing guarantees that such a next-step model is formally a refinement of the previous one. Our work is set within the declarative, event-based process modelling language of timed Dynamic Condition Response (DCR) graphs, which can express timed constraints (conditions with delay and obligations with deadlines) between events, liveness, safety, and concurrency. Concretely, we extend DCR graph syntax and semantics with a notion of subprocess, provide examples of its use, and give sound approximations of situations where replacing an event with a subprocess formally is a refinement of the original process.

OriginalsprogEngelsk
TitelBusiness Process Management - 19th International Conference, BPM 2021, Proceedings
RedaktørerArtem Polyvyanyy, Moe Thandar Wynn, Amy Van Looy, Manfred Reichert
ForlagSpringer
Publikationsdato2021
Sider161-178
ISBN (Trykt)9783030854683
DOI
StatusUdgivet - 2021
Begivenhed19th International Conference on Business Process Management, BPM 2021 - Rome, Italien
Varighed: 6 sep. 202110 sep. 2021

Konference

Konference19th International Conference on Business Process Management, BPM 2021
Land/OmrådeItalien
ByRome
Periode06/09/202110/09/2021
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind12875 LNCS
ISSN0302-9743

Bibliografisk note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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