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

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 use...

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Detalles Bibliográficos
Autor principal: Asteasuain, Fernando
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2022
Materias:
Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/149578
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-149578
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
spellingShingle Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
Asteasuain, Fernando
A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
topic_facet Ciencias Informáticas
Formal Verification
BIG DATA
Metamorphic Testing
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.
format Objeto de conferencia
Objeto de conferencia
author Asteasuain, Fernando
author_facet Asteasuain, Fernando
author_sort Asteasuain, Fernando
title A flexible and expressive formalism to specify Metamorphic Properties for BIG DATA systems validation
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 flexible and expressive formalism to specify metamorphic properties for big data systems validation
publishDate 2022
url http://sedici.unlp.edu.ar/handle/10915/149578
work_keys_str_mv AT asteasuainfernando aflexibleandexpressiveformalismtospecifymetamorphicpropertiesforbigdatasystemsvalidation
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bdutipo_str Repositorios
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