Subjectivity reducing in software version criticality classification with the support of an expert system
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/25132 |
Resumo: | In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version. |
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Subjectivity reducing in software version criticality classification with the support of an expert systemReducción de la subjetividad en la clasificación de versiones de software con el apoyo de un sistema expertoRedução de subjetividade na classificação de versão de software com apoio de um sistema especialistaReducción de subjetividadClasificación de CriticidadSistema ExpertoLanzamiento de la Versión del SoftwareIndicadores clave de rendimiento.Redução de subjetividadeClassificação de criticidadeSistema EspecialistaLiberação de Versão de SoftwareIndicadores-chave de desempenho.Subjectivity ReductionCriticality ClassificationExpert SystemSoftware Version ReleaseKey performance-indicators.In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version.En el proceso de gestión de liberación de versiones de software, existe la necesidad, por parte de especialistas humanos, de clasificar la criticidad de cada versión de software. Sin embargo, la subjetividad de esta clasificación puede estar presente según la experiencia adquirida por los especialistas a lo largo de los años. Con el fin de reducir la subjetividad en el proceso, se puede aplicar una técnica de Inteligencia Artificial llamada Specialist System (ES) para representar el conocimiento de especialistas humanos y utilizarlo en la resolución de problemas. Así, el objetivo de este artículo fue reducir la subjetividad en la clasificación de criticidad de la versión del software con el apoyo del Sistema Experto. Por lo tanto, se diseñó un cuestionario con el objetivo de obtener opiniones críticas clasificadas en Alta, Media y Baja en la versión del software de cada especialista para ayudar en la elaboración de las reglas de producción de EE. ES generó 17 reglas de producción con un nivel de confianza del 100% aplicado a una base de datos de producción. Los resultados de la clasificación realizada por la SE correspondieron a la clasificación realizada por los especialistas en la base de producción, es decir, la SE logró representar sus conocimientos. Luego, se aplicó otro cuestionario a especialistas para verificar la percepción de satisfacción con respecto al uso de la ES con un resultado obtenido de 4.8, considerado satisfactorio. Se concluyó, entonces, que la SE apoyó la reducción de la subjetividad en la clasificación de la criticidad de la versión del software.No processo de gerenciamento de liberação de versão de software, há necessidade, por parte de especialistas humanos, de classificar a criticidade de cada versão de software. No entanto, a subjetividade dessa classificação pode estar presente de acordo com a experiência adquirida por especialistas ao longo dos anos. Com o objetivo de reduzir a subjetividade no processo, uma técnica de Inteligência Artificial denominada Sistema Especialista (ES) pode ser aplicada para representar o conhecimento de especialistas humanos e utilizá-lo na resolução de problemas. Assim, o objetivo deste artigo foi reduzir a subjetividade na classificação da criticidade da versão do software com o apoio do Sistema Especialista. Para tanto, foi elaborado um questionário com o objetivo de obter as opiniões de criticidade classificadas em Alta, Média e Baixa na versão de software de cada especialista para auxiliar na elaboração das regras de produção do ES. O ES gerou 17 regras de produção com um nível de confiança de 100% aplicado a um banco de dados de produção. Os resultados da classificação realizada pelo SE corresponderam à classificação realizada pelos especialistas na base de produção, ou seja, o SE conseguiu representar os seus conhecimentos. Em seguida, outro questionário foi aplicado aos especialistas para verificar a percepção de satisfação em relação ao uso do SE com um resultado obtido de 4,8, considerado satisfatório. Concluiu-se, então, que o SE apoiou a redução da subjetividade na classificação da criticidade da versão do software.Research, Society and Development2022-01-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2513210.33448/rsd-v11i1.25132Research, Society and Development; Vol. 11 No. 1; e37811125132Research, Society and Development; Vol. 11 Núm. 1; e37811125132Research, Society and Development; v. 11 n. 1; e378111251322525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/25132/21983Copyright (c) 2022 Dacyr Dante de Oliveira Gatto; Renato José Sassihttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGatto, Dacyr Dante de Oliveira Sassi, Renato José 2022-01-16T18:08:18Zoai:ojs.pkp.sfu.ca:article/25132Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:43:29.454005Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Subjectivity reducing in software version criticality classification with the support of an expert system Reducción de la subjetividad en la clasificación de versiones de software con el apoyo de un sistema experto Redução de subjetividade na classificação de versão de software com apoio de um sistema especialista |
title |
Subjectivity reducing in software version criticality classification with the support of an expert system |
spellingShingle |
Subjectivity reducing in software version criticality classification with the support of an expert system Gatto, Dacyr Dante de Oliveira Reducción de subjetividad Clasificación de Criticidad Sistema Experto Lanzamiento de la Versión del Software Indicadores clave de rendimiento. Redução de subjetividade Classificação de criticidade Sistema Especialista Liberação de Versão de Software Indicadores-chave de desempenho. Subjectivity Reduction Criticality Classification Expert System Software Version Release Key performance-indicators. |
title_short |
Subjectivity reducing in software version criticality classification with the support of an expert system |
title_full |
Subjectivity reducing in software version criticality classification with the support of an expert system |
title_fullStr |
Subjectivity reducing in software version criticality classification with the support of an expert system |
title_full_unstemmed |
Subjectivity reducing in software version criticality classification with the support of an expert system |
title_sort |
Subjectivity reducing in software version criticality classification with the support of an expert system |
author |
Gatto, Dacyr Dante de Oliveira |
author_facet |
Gatto, Dacyr Dante de Oliveira Sassi, Renato José |
author_role |
author |
author2 |
Sassi, Renato José |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Gatto, Dacyr Dante de Oliveira Sassi, Renato José |
dc.subject.por.fl_str_mv |
Reducción de subjetividad Clasificación de Criticidad Sistema Experto Lanzamiento de la Versión del Software Indicadores clave de rendimiento. Redução de subjetividade Classificação de criticidade Sistema Especialista Liberação de Versão de Software Indicadores-chave de desempenho. Subjectivity Reduction Criticality Classification Expert System Software Version Release Key performance-indicators. |
topic |
Reducción de subjetividad Clasificación de Criticidad Sistema Experto Lanzamiento de la Versión del Software Indicadores clave de rendimiento. Redução de subjetividade Classificação de criticidade Sistema Especialista Liberação de Versão de Software Indicadores-chave de desempenho. Subjectivity Reduction Criticality Classification Expert System Software Version Release Key performance-indicators. |
description |
In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-09 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25132 10.33448/rsd-v11i1.25132 |
url |
https://rsdjournal.org/index.php/rsd/article/view/25132 |
identifier_str_mv |
10.33448/rsd-v11i1.25132 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25132/21983 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Dacyr Dante de Oliveira Gatto; Renato José Sassi https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Dacyr Dante de Oliveira Gatto; Renato José Sassi https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 11 No. 1; e37811125132 Research, Society and Development; Vol. 11 Núm. 1; e37811125132 Research, Society and Development; v. 11 n. 1; e37811125132 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
_version_ |
1797052761369477120 |