Declare MoGeS: Model Generator and Specializer

Manal Laghmouch; Benoît Depaire; Nicola Gigante; Mieke Jans; Marco Montali

Declare MoGeS: Model Generator and Specializer

Manal Laghmouch^*, Benoît Depaire, Nicola Gigante, Mieke Jans, Marco Montali

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

This demo introduces Declare MoGeS, an automated approach for generating and specializing Declare process models that can be employed as input for log generation. The specialization of Declare models is particularly interesting to produce event logs that encompass a subset of the behavior of other logs. Declare MoGeS seamlessly integrates with existing log generators, streamlining the log generation process.

Original language	English
Title of host publication	CEUR Workshop Proceedings
Subtitle of host publication	ICPM Doctoral Consortium and Demo Track 2023
Editors	Jan Martijn E.M. van der Werf, Cristina Cabanillas, Francesco Leotta, Laura Genga
Publisher	CEUR-WS.org
Number of pages	5
Volume	3648
Publication status	Published - 2023
Event	Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 - Rome, Italy Duration: 27 Oct 2023 → 27 Oct 2023 https://icpmconference.org/2023/doctoral-consortium/

Publication series

Series	CEUR Workshop Proceedings
ISSN	1613-0073

Conference

Conference	Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023
Country/Territory	Italy
City	Rome
Period	27/10/23 → 27/10/23
Internet address	https://icpmconference.org/2023/doctoral-consortium/

Keywords

Declare
Linear Temporal Logic
Model Generation
Model Specialization

Access to Document

https://ceur-ws.org/Vol-3648/paper_7567.pdfLicence: CC BY

Cite this

@inproceedings{18e7efa85a5740c8ba78310f6315cda0,

title = "Declare MoGeS: Model Generator and Specializer",

abstract = "This demo introduces Declare MoGeS, an automated approach for generating and specializing Declare process models that can be employed as input for log generation. The specialization of Declare models is particularly interesting to produce event logs that encompass a subset of the behavior of other logs. Declare MoGeS seamlessly integrates with existing log generators, streamlining the log generation process.",

keywords = "Declare, Linear Temporal Logic, Model Generation, Model Specialization",

author = "Manal Laghmouch and Beno{\^i}t Depaire and Nicola Gigante and Mieke Jans and Marco Montali",

note = "data source:; Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 ; Conference date: 27-10-2023 Through 27-10-2023",

year = "2023",

language = "English",

volume = "3648",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS.org",

editor = "{van der Werf}, {Jan Martijn E.M.} and Cristina Cabanillas and Francesco Leotta and Laura Genga",

booktitle = "CEUR Workshop Proceedings",

address = "Germany",

url = "https://icpmconference.org/2023/doctoral-consortium/",

}

Laghmouch, M, Depaire, B, Gigante, N, Jans, M & Montali, M 2023, Declare MoGeS: Model Generator and Specializer. in JMEM van der Werf, C Cabanillas, F Leotta & L Genga (eds), CEUR Workshop Proceedings: ICPM Doctoral Consortium and Demo Track 2023. vol. 3648, CEUR-WS.org, CEUR Workshop Proceedings, Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023, Rome, Italy, 27/10/23. <https://ceur-ws.org/Vol-3648/paper_7567.pdf>

Declare MoGeS: Model Generator and Specializer. / Laghmouch, Manal; Depaire, Benoît; Gigante, Nicola et al.
CEUR Workshop Proceedings: ICPM Doctoral Consortium and Demo Track 2023. ed. / Jan Martijn E.M. van der Werf; Cristina Cabanillas; Francesco Leotta; Laura Genga. Vol. 3648 CEUR-WS.org, 2023. (CEUR Workshop Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - Declare MoGeS

T2 - Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023

AU - Laghmouch, Manal

AU - Depaire, Benoît

AU - Gigante, Nicola

AU - Jans, Mieke

AU - Montali, Marco

N1 - data source:

PY - 2023

Y1 - 2023

N2 - This demo introduces Declare MoGeS, an automated approach for generating and specializing Declare process models that can be employed as input for log generation. The specialization of Declare models is particularly interesting to produce event logs that encompass a subset of the behavior of other logs. Declare MoGeS seamlessly integrates with existing log generators, streamlining the log generation process.

AB - This demo introduces Declare MoGeS, an automated approach for generating and specializing Declare process models that can be employed as input for log generation. The specialization of Declare models is particularly interesting to produce event logs that encompass a subset of the behavior of other logs. Declare MoGeS seamlessly integrates with existing log generators, streamlining the log generation process.

KW - Declare

KW - Linear Temporal Logic

KW - Model Generation

KW - Model Specialization

M3 - Conference article in proceeding

VL - 3648

T3 - CEUR Workshop Proceedings

BT - CEUR Workshop Proceedings

A2 - van der Werf, Jan Martijn E.M.

A2 - Cabanillas, Cristina

A2 - Leotta, Francesco

A2 - Genga, Laura

PB - CEUR-WS.org

Y2 - 27 October 2023 through 27 October 2023

ER -