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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/149578
Ver los metadatos del registro completo
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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:UNLP2025-09-29T11:38:22Zoai: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:13292025-09-29 11:38:23.02SEDICI (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 |
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http://sedici.unlp.edu.ar/handle/10915/149578 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 282-291 |
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