Maximal and minimal dynamic Petri net slicing

[EN] Context: Petri net slicing is a technique to reduce the size of a Petri net to ease the analysis or understanding of the original Petri net. Objective: Presenting two new Petri net slicing algorithms to isolate those places and transitions of a Petri net (the slice) that may contribute tokens t...

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Autores: Llorens Agost, María Luisa|||0000-0002-2790-0055, Oliver Villarroya, Javier|||0000-0002-1169-1260, Silva, Josep|||0000-0001-5096-0008, Tamarit, S.
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/214670
Acceso en línea:https://riunet.upv.es/handle/10251/214670
Access Level:acceso abierto
Palabra clave:Petri nets
Program slicing
Petri net slicing
LENGUAJES Y SISTEMAS INFORMATICOS
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spelling Maximal and minimal dynamic Petri net slicingLlorens Agost, María Luisa|||0000-0002-2790-0055Oliver Villarroya, Javier|||0000-0002-1169-1260Silva, Josep|||0000-0001-5096-0008Tamarit, S.Petri netsProgram slicingPetri net slicingLENGUAJES Y SISTEMAS INFORMATICOS[EN] Context: Petri net slicing is a technique to reduce the size of a Petri net to ease the analysis or understanding of the original Petri net. Objective: Presenting two new Petri net slicing algorithms to isolate those places and transitions of a Petri net (the slice) that may contribute tokens to one or more places given (the slicing criterion). Method: The two algorithms proposed are formalized. The maximality of the first algorithm and the minimality of the second algorithm are formally proven. Both algorithms together with three other state-of-the-art algorithms have been implemented and integrated into a single tool so that we have been able to carry out a fair empirical evaluation. Results: Besides the two new Petri net slicing algorithms, a public, free, and open-source implementation of five algorithms is reported. The results of an empirical evaluation of the new algorithms and the slices they produce are also presented. Conclusions: The first algorithm collects all places and transitions that may contribute tokens (in any computation) to the slicing criterion, while the second algorithm collects the places and transitions needed to fire the shortest transition sequence that contributes tokens to some place in the slicing criterion. Therefore, the net computed by the first algorithm can reproduce any computation that contributes tokens to any place of interest. In contrast, the second algorithm loses this possibility, but it often produces a much more reduced subnet (which still can reproduce some computations that contribute tokens to some places of interest). The first algorithm is proven maximal, and the second one is proven minimal.This work has been partially supported by the EU (FEDER) and the Spanish MCI/AEI under grant PID2019-104735RB-C41 and by the European Union's Horizon 2020 research and innovation programme under grant agreement No 952215 (Tailor).IOS PressEscuela Técnica Superior de Ingeniería de TelecomunicaciónDepartamento de Sistemas Informáticos y ComputaciónEscuela Técnica Superior de Ingeniería InformáticaInstituto Universitario Valenciano de Investigación en Inteligencia ArtificialEuropean CommissionAGENCIA ESTATAL DE INVESTIGACIONEuropean Regional Development FundRepositorio Institucional de la Universitat Politècnica de València Riunet20232023-06-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/214670reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengEuropean Commission https://doi.org/10.13039/501100000780 H2020 952215 Integrating Reasoning, Learning and OptimizationAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 PID2019-104735RB-C41 SAFER-UPV: ANALISIS Y VALIDACION DE SOFTWARE Y RECURSOS WEBopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2146702026-06-13T07:49:27Z
dc.title.none.fl_str_mv Maximal and minimal dynamic Petri net slicing
title Maximal and minimal dynamic Petri net slicing
spellingShingle Maximal and minimal dynamic Petri net slicing
Llorens Agost, María Luisa|||0000-0002-2790-0055
Petri nets
Program slicing
Petri net slicing
LENGUAJES Y SISTEMAS INFORMATICOS
title_short Maximal and minimal dynamic Petri net slicing
title_full Maximal and minimal dynamic Petri net slicing
title_fullStr Maximal and minimal dynamic Petri net slicing
title_full_unstemmed Maximal and minimal dynamic Petri net slicing
title_sort Maximal and minimal dynamic Petri net slicing
dc.creator.none.fl_str_mv Llorens Agost, María Luisa|||0000-0002-2790-0055
Oliver Villarroya, Javier|||0000-0002-1169-1260
Silva, Josep|||0000-0001-5096-0008
Tamarit, S.
author Llorens Agost, María Luisa|||0000-0002-2790-0055
author_facet Llorens Agost, María Luisa|||0000-0002-2790-0055
Oliver Villarroya, Javier|||0000-0002-1169-1260
Silva, Josep|||0000-0001-5096-0008
Tamarit, S.
author_role author
author2 Oliver Villarroya, Javier|||0000-0002-1169-1260
Silva, Josep|||0000-0001-5096-0008
Tamarit, S.
author2_role author
author
author
dc.contributor.none.fl_str_mv Escuela Técnica Superior de Ingeniería de Telecomunicación
Departamento de Sistemas Informáticos y Computación
Escuela Técnica Superior de Ingeniería Informática
Instituto Universitario Valenciano de Investigación en Inteligencia Artificial
European Commission
AGENCIA ESTATAL DE INVESTIGACION
European Regional Development Fund
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Petri nets
Program slicing
Petri net slicing
LENGUAJES Y SISTEMAS INFORMATICOS
topic Petri nets
Program slicing
Petri net slicing
LENGUAJES Y SISTEMAS INFORMATICOS
description [EN] Context: Petri net slicing is a technique to reduce the size of a Petri net to ease the analysis or understanding of the original Petri net. Objective: Presenting two new Petri net slicing algorithms to isolate those places and transitions of a Petri net (the slice) that may contribute tokens to one or more places given (the slicing criterion). Method: The two algorithms proposed are formalized. The maximality of the first algorithm and the minimality of the second algorithm are formally proven. Both algorithms together with three other state-of-the-art algorithms have been implemented and integrated into a single tool so that we have been able to carry out a fair empirical evaluation. Results: Besides the two new Petri net slicing algorithms, a public, free, and open-source implementation of five algorithms is reported. The results of an empirical evaluation of the new algorithms and the slices they produce are also presented. Conclusions: The first algorithm collects all places and transitions that may contribute tokens (in any computation) to the slicing criterion, while the second algorithm collects the places and transitions needed to fire the shortest transition sequence that contributes tokens to some place in the slicing criterion. Therefore, the net computed by the first algorithm can reproduce any computation that contributes tokens to any place of interest. In contrast, the second algorithm loses this possibility, but it often produces a much more reduced subnet (which still can reproduce some computations that contribute tokens to some places of interest). The first algorithm is proven maximal, and the second one is proven minimal.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-06-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/214670
url https://riunet.upv.es/handle/10251/214670
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission https://doi.org/10.13039/501100000780 H2020 952215 Integrating Reasoning, Learning and Optimization
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 PID2019-104735RB-C41 SAFER-UPV: ANALISIS Y VALIDACION DE SOFTWARE Y RECURSOS WEB
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOS Press
publisher.none.fl_str_mv IOS Press
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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