Identification of user stories in software issues records applying pre-trained natural language processing models

Autores
Peña, Francisco Javier; Roldán, María Luciana; Vegetti, María Marcela
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the last decades, agile development methods have been increasingly adopted by the software industry. User stories are one of the primary development artifacts for agile project teams. Issue Management Systems are widely used by software development teams to generate user stories, and organize them in meaningful fragments: epics, themes, and sprints. In addition, these tools enable generating any kind of issues, like bugs, change requests, tasks, etc. The responsibility for correctly categorizing an issue is in the hands of the team members, so it is a task prone to errors and frequently omitted due to lack of time or bad practices. Thus, a current problem is that many issues in projects remain uncategorized or mislabeled. Several studies have shown that it is common to find the uncategorized user stories of a software project in large volumes of issues records maintained by Issue Management Systems. In this work, we present two Neural Network models for text classification that were implemented for the identification of user stories in issue records.
Fil: Peña, Francisco Javier. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Roldán, María Luciana. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Vegetti, María Marcela. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-03-26T20:35:15Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/10133
Acceder
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spelling Identification of user stories in software issues records applying pre-trained natural language processing modelsPeña, Francisco JavierRoldán, María LucianaVegetti, María MarcelaIn the last decades, agile development methods have been increasingly adopted by the software industry. User stories are one of the primary development artifacts for agile project teams. Issue Management Systems are widely used by software development teams to generate user stories, and organize them in meaningful fragments: epics, themes, and sprints. In addition, these tools enable generating any kind of issues, like bugs, change requests, tasks, etc. The responsibility for correctly categorizing an issue is in the hands of the team members, so it is a task prone to errors and frequently omitted due to lack of time or bad practices. Thus, a current problem is that many issues in projects remain uncategorized or mislabeled. Several studies have shown that it is common to find the uncategorized user stories of a software project in large volumes of issues records maintained by Issue Management Systems. In this work, we present two Neural Network models for text classification that were implemented for the identification of user stories in issue records.Fil: Peña, Francisco Javier. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.Fil: Roldán, María Luciana. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.Fil: Vegetti, María Marcela. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.8º CONAIISI2024-03-26T20:35:15Z2024-03-26T20:35:15Z2020-12info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciapdfapplication/pdfPeña, F.J.: Roldán, M.L. & Vegetti, M.M. (5 y 6 de Noviembre de 2020). Identification of user stories in software issues records applying pre-trained natural language processing models. 8vo. Congreso Nacional de Ingeniería Informática / Sistemas de Información (CONAIISI 2020). UTN. Facultad Regional San Francisco, Argentinahttp://hdl.handle.net/20.500.12272/10133engSIUTIFE0005514TC - Sistema de recomendación de prácticas ágiles basado en ontologías y aprendizaje automáticoinfo:eu-repo/semantics/openAccess2024-03-26T20:35:15Zhttp://creativecommons.org/licenses/by/4.0/Atribución 4.0 InternacionalLos autoresCreativeCommonsreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:45:37Zoai:ria.utn.edu.ar:20.500.12272/10133instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:45:38.644Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Identification of user stories in software issues records applying pre-trained natural language processing models
title Identification of user stories in software issues records applying pre-trained natural language processing models
spellingShingle Identification of user stories in software issues records applying pre-trained natural language processing models
Peña, Francisco Javier
title_short Identification of user stories in software issues records applying pre-trained natural language processing models
title_full Identification of user stories in software issues records applying pre-trained natural language processing models
title_fullStr Identification of user stories in software issues records applying pre-trained natural language processing models
title_full_unstemmed Identification of user stories in software issues records applying pre-trained natural language processing models
title_sort Identification of user stories in software issues records applying pre-trained natural language processing models
dc.creator.none.fl_str_mv Peña, Francisco Javier
Roldán, María Luciana
Vegetti, María Marcela
author Peña, Francisco Javier
author_facet Peña, Francisco Javier
Roldán, María Luciana
Vegetti, María Marcela
author_role author
author2 Roldán, María Luciana
Vegetti, María Marcela
author2_role author
author
dc.description.none.fl_txt_mv In the last decades, agile development methods have been increasingly adopted by the software industry. User stories are one of the primary development artifacts for agile project teams. Issue Management Systems are widely used by software development teams to generate user stories, and organize them in meaningful fragments: epics, themes, and sprints. In addition, these tools enable generating any kind of issues, like bugs, change requests, tasks, etc. The responsibility for correctly categorizing an issue is in the hands of the team members, so it is a task prone to errors and frequently omitted due to lack of time or bad practices. Thus, a current problem is that many issues in projects remain uncategorized or mislabeled. Several studies have shown that it is common to find the uncategorized user stories of a software project in large volumes of issues records maintained by Issue Management Systems. In this work, we present two Neural Network models for text classification that were implemented for the identification of user stories in issue records.
Fil: Peña, Francisco Javier. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Roldán, María Luciana. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Vegetti, María Marcela. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
description In the last decades, agile development methods have been increasingly adopted by the software industry. User stories are one of the primary development artifacts for agile project teams. Issue Management Systems are widely used by software development teams to generate user stories, and organize them in meaningful fragments: epics, themes, and sprints. In addition, these tools enable generating any kind of issues, like bugs, change requests, tasks, etc. The responsibility for correctly categorizing an issue is in the hands of the team members, so it is a task prone to errors and frequently omitted due to lack of time or bad practices. Thus, a current problem is that many issues in projects remain uncategorized or mislabeled. Several studies have shown that it is common to find the uncategorized user stories of a software project in large volumes of issues records maintained by Issue Management Systems. In this work, we present two Neural Network models for text classification that were implemented for the identification of user stories in issue records.
publishDate 2020
dc.date.none.fl_str_mv 2020-12
2024-03-26T20:35:15Z
2024-03-26T20:35:15Z
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv Peña, F.J.: Roldán, M.L. & Vegetti, M.M. (5 y 6 de Noviembre de 2020). Identification of user stories in software issues records applying pre-trained natural language processing models. 8vo. Congreso Nacional de Ingeniería Informática / Sistemas de Información (CONAIISI 2020). UTN. Facultad Regional San Francisco, Argentina
http://hdl.handle.net/20.500.12272/10133
identifier_str_mv Peña, F.J.: Roldán, M.L. & Vegetti, M.M. (5 y 6 de Noviembre de 2020). Identification of user stories in software issues records applying pre-trained natural language processing models. 8vo. Congreso Nacional de Ingeniería Informática / Sistemas de Información (CONAIISI 2020). UTN. Facultad Regional San Francisco, Argentina
url http://hdl.handle.net/20.500.12272/10133
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv SIUTIFE0005514TC - Sistema de recomendación de prácticas ágiles basado en ontologías y aprendizaje automático
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-03-26T20:35:15Z
http://creativecommons.org/licenses/by/4.0/
Atribución 4.0 Internacional
Los autores
CreativeCommons
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-03-26T20:35:15Z
http://creativecommons.org/licenses/by/4.0/
Atribución 4.0 Internacional
Los autores
CreativeCommons
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv 8º CONAIISI
publisher.none.fl_str_mv 8º CONAIISI
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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