A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation

Autores
Asteasuain, Fernando
Año de publicación
2022
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
BIG DATA systems represent a huge challenge for software engineering validations tasks since they have been classified as “non testable”. Metamorphic Relationships (MR) have been proposed as a technique to overcome this problem. These relationships establish interactions between data that can be used to validate the expected behavior of the system. However, the process of exploring and defining MRs is a very arduous one, and an expressive and flexible specification language is needed to denote them. In this work we show how the Feather Weight Visual Scenarios (FVS) framework can be seen as an appealing tool to specify MRs. We exploit FVS features to model complex MR interactions and analysis, allowing the possibility to perform non trivial operations between MRs such as refinement and consistency checking. FVS is shown in action by introducing a proof of concept example focused on a machine learning system over biology cell images.
XIX Workshop Ingeniería de Software (WIS)
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/149578
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/149578
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validationAsteasuain, FernandoCiencias InformáticasFormal VerificationBIG DATAMetamorphic TestingBIG DATA systems represent a huge challenge for software engineering validations tasks since they have been classified as “non testable”. Metamorphic Relationships (MR) have been proposed as a technique to overcome this problem. These relationships establish interactions between data that can be used to validate the expected behavior of the system. However, the process of exploring and defining MRs is a very arduous one, and an expressive and flexible specification language is needed to denote them. In this work we show how the Feather Weight Visual Scenarios (FVS) framework can be seen as an appealing tool to specify MRs. We exploit FVS features to model complex MR interactions and analysis, allowing the possibility to perform non trivial operations between MRs such as refinement and consistency checking. FVS is shown in action by introducing a proof of concept example focused on a machine learning system over biology cell images.XIX Workshop Ingeniería de Software (WIS)Red de Universidades con Carreras en Informática2022-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf282-291http://sedici.unlp.edu.ar/handle/10915/149578enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-1364-31-2info:eu-repo/semantics/reference/hdl/10915/149102info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:30:11Zoai:sedici.unlp.edu.ar:10915/149578Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:30:12.077SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
title A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
spellingShingle A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
Asteasuain, Fernando
Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
title_short A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
title_full A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
title_fullStr A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
title_full_unstemmed A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
title_sort A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
dc.creator.none.fl_str_mv Asteasuain, Fernando
author Asteasuain, Fernando
author_facet Asteasuain, Fernando
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
topic Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
dc.description.none.fl_txt_mv BIG DATA systems represent a huge challenge for software engineering validations tasks since they have been classified as “non testable”. Metamorphic Relationships (MR) have been proposed as a technique to overcome this problem. These relationships establish interactions between data that can be used to validate the expected behavior of the system. However, the process of exploring and defining MRs is a very arduous one, and an expressive and flexible specification language is needed to denote them. In this work we show how the Feather Weight Visual Scenarios (FVS) framework can be seen as an appealing tool to specify MRs. We exploit FVS features to model complex MR interactions and analysis, allowing the possibility to perform non trivial operations between MRs such as refinement and consistency checking. FVS is shown in action by introducing a proof of concept example focused on a machine learning system over biology cell images.
XIX Workshop Ingeniería de Software (WIS)
Red de Universidades con Carreras en Informática
description BIG DATA systems represent a huge challenge for software engineering validations tasks since they have been classified as “non testable”. Metamorphic Relationships (MR) have been proposed as a technique to overcome this problem. These relationships establish interactions between data that can be used to validate the expected behavior of the system. However, the process of exploring and defining MRs is a very arduous one, and an expressive and flexible specification language is needed to denote them. In this work we show how the Feather Weight Visual Scenarios (FVS) framework can be seen as an appealing tool to specify MRs. We exploit FVS features to model complex MR interactions and analysis, allowing the possibility to perform non trivial operations between MRs such as refinement and consistency checking. FVS is shown in action by introducing a proof of concept example focused on a machine learning system over biology cell images.
publishDate 2022
dc.date.none.fl_str_mv 2022-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/149578
url http://sedici.unlp.edu.ar/handle/10915/149578
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-1364-31-2
info:eu-repo/semantics/reference/hdl/10915/149102
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
282-291
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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