Context-Aware Verification of DMN

S Vandevelde; B Callewaert; J Vennekens

Context-Aware Verification of DMN

S Vandevelde
, B Callewaert
, J Vennekens

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

1 Citation (Scopus)

Abstract

The Decision Model and Notation (DMN) standard is a user-friendly notation for decision logic. To verify correctness of DMN decision tables, many tools are available. However, most of these look at a table in isolation, with little or no regards for its context. In this work, we argue for the importance of context, and extend the formal verification criteria to include it. We identify two forms of context, namely in-model context and background knowledge. We also present our own context-aware verification tool, implemented in our DMN-IDP interface, and show that this context-aware approach allows us to perform more thorough verification than any other available tool.

Original language	English
Title of host publication	Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
Editors	TX Bui
Publisher	ScholarSpace
Pages	6239-6246
Number of pages	8
ISBN (Electronic)	9780998133157
ISBN (Print)	978-0-9981331-5-7
Publication status	Published - 4 Jan 2022
Externally published	Yes

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
Volume	2022-January
ISSN (Print)	1530-1605

Bibliographical note

Funding Information:
This∗ research received funding from the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” programme

Publisher Copyright:
© 2022 IEEE Computer Society. All rights reserved.

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Cite this

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title = "Context-Aware Verification of DMN",

abstract = "The Decision Model and Notation (DMN) standard is a user-friendly notation for decision logic. To verify correctness of DMN decision tables, many tools are available. However, most of these look at a table in isolation, with little or no regards for its context. In this work, we argue for the importance of context, and extend the formal verification criteria to include it. We identify two forms of context, namely in-model context and background knowledge. We also present our own context-aware verification tool, implemented in our DMN-IDP interface, and show that this context-aware approach allows us to perform more thorough verification than any other available tool.",

author = "S Vandevelde and B Callewaert and J Vennekens",

note = "Funding Information: This∗ research received funding from the Flemish Government under the “Onderzoeksprogramma Artifici{\"e}le Intelligentie (AI) Vlaanderen” programme Publisher Copyright: {\textcopyright} 2022 IEEE Computer Society. All rights reserved.",

year = "2022",

month = jan,

day = "4",

language = "English",

isbn = "978-0-9981331-5-7",

series = "Proceedings of the Annual Hawaii International Conference on System Sciences",

publisher = "ScholarSpace",

pages = "6239--6246",

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booktitle = "Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022",

}

Context-Aware Verification of DMN. / Vandevelde, S; Callewaert, B; Vennekens, J.
Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022. ed. / TX Bui. ScholarSpace, 2022. p. 6239-6246 (Proceedings of the Annual Hawaii International Conference on System Sciences; Vol. 2022-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

TY - GEN

T1 - Context-Aware Verification of DMN

AU - Vandevelde, S

AU - Callewaert, B

AU - Vennekens, J

N1 - Funding Information: This∗ research received funding from the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” programme Publisher Copyright: © 2022 IEEE Computer Society. All rights reserved.

PY - 2022/1/4

Y1 - 2022/1/4

N2 - The Decision Model and Notation (DMN) standard is a user-friendly notation for decision logic. To verify correctness of DMN decision tables, many tools are available. However, most of these look at a table in isolation, with little or no regards for its context. In this work, we argue for the importance of context, and extend the formal verification criteria to include it. We identify two forms of context, namely in-model context and background knowledge. We also present our own context-aware verification tool, implemented in our DMN-IDP interface, and show that this context-aware approach allows us to perform more thorough verification than any other available tool.

AB - The Decision Model and Notation (DMN) standard is a user-friendly notation for decision logic. To verify correctness of DMN decision tables, many tools are available. However, most of these look at a table in isolation, with little or no regards for its context. In this work, we argue for the importance of context, and extend the formal verification criteria to include it. We identify two forms of context, namely in-model context and background knowledge. We also present our own context-aware verification tool, implemented in our DMN-IDP interface, and show that this context-aware approach allows us to perform more thorough verification than any other available tool.

UR - https://www.scopus.com/pages/publications/85142648804

M3 - Conference paper

SN - 978-0-9981331-5-7

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 6239

EP - 6246

BT - Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022

A2 - Bui, TX

PB - ScholarSpace

ER -

Context-Aware Verification of DMN

Abstract

Publication series

Bibliographical note

Handle.net

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