VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software

Introducción: Académicos, desarrolladores y empresas enfocadas en el desarrollo tecnológico, buscan conocer lo que ya existe y lo que aún falta en este campo. Una de las formas que utilizan, es realizar revisiones sobre fuentes bibliográficas (estado del arte). En este sentido, se desarrolló una her...

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Autores:
Hidalgo-Suarez, Carlos Giovanny
Bucheli-Guerrero , Victor Andres
Ordoñez-Eraso , Hugo Armando
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/12353
Acceso en línea:
https://hdl.handle.net/11323/12353
https://doi.org/10.17981/ingecuc.18.1.2022.07
Palabra clave:
Mining Software Repositories
Technology Forecasting
Review of technologies
Technological maps
GitHub
Minería de Repositorios de Software
Vigilancia Tecnológica
Revisión del estado de la técnica
Mapas tecnológicos
GitHub
Rights
openAccess
License
INGE CUC - 2021
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oai_identifier_str oai:repositorio.cuc.edu.co:11323/12353
network_acronym_str RCUC2
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repository_id_str
dc.title.spa.fl_str_mv VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
dc.title.translated.eng.fl_str_mv VIGHUB: a Technology Forecasting Tool based on Mining Software Repositories
title VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
spellingShingle VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
Mining Software Repositories
Technology Forecasting
Review of technologies
Technological maps
GitHub
Minería de Repositorios de Software
Vigilancia Tecnológica
Revisión del estado de la técnica
Mapas tecnológicos
GitHub
title_short VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
title_full VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
title_fullStr VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
title_full_unstemmed VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
title_sort VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software
dc.creator.fl_str_mv Hidalgo-Suarez, Carlos Giovanny
Bucheli-Guerrero , Victor Andres
Ordoñez-Eraso , Hugo Armando
dc.contributor.author.spa.fl_str_mv Hidalgo-Suarez, Carlos Giovanny
Bucheli-Guerrero , Victor Andres
Ordoñez-Eraso , Hugo Armando
dc.subject.eng.fl_str_mv Mining Software Repositories
Technology Forecasting
Review of technologies
Technological maps
GitHub
topic Mining Software Repositories
Technology Forecasting
Review of technologies
Technological maps
GitHub
Minería de Repositorios de Software
Vigilancia Tecnológica
Revisión del estado de la técnica
Mapas tecnológicos
GitHub
dc.subject.spa.fl_str_mv Minería de Repositorios de Software
Vigilancia Tecnológica
Revisión del estado de la técnica
Mapas tecnológicos
GitHub
description Introducción: Académicos, desarrolladores y empresas enfocadas en el desarrollo tecnológico, buscan conocer lo que ya existe y lo que aún falta en este campo. Una de las formas que utilizan, es realizar revisiones sobre fuentes bibliográficas (estado del arte). En este sentido, se desarrolló una herramienta que permite identificar el estado actual de una tecnología de forma semi-automática. Objetivo: Este artículo propone una herramienta que extrae información de repositorios alojados en GitHub. Analiza los datos utilizando técnicas computacionales y presenta los resultados a través de visualizaciones que identifican la evolución tecnológica del campo estudiado a través de los lenguajes de programación, principales, repositorios y organizaciones. Metodología: Se utiliza un modelo basado en Repositorios de Software de Minería (MSR), el cual integra una arquitectura basada en microservicios utilizando diferentes lenguajes de programación, lo que permitió la construcción de la herramienta VigHub. El modelo se centra en cuatro aspectos: selección de un tema tecnológico, extracción de la fuente de datos, análisis de la información mediante técnicas computacionales y finalmente, se muestran los resultados a través de visualizaciones. Resultados: Se dispuso la herramienta VigHub de manera online para realizar 3 casos de estudio. El primero en la academia, donde se identifico desde el año 2011 al 2021, las tecnologías, los lenguajes de programación, los usuarios y empresas interesadas en el desarrollo de VLE’s (Virtual Learning Environment). El segundo y tercero fueron ejecutados por empresas (ambiente industrial), que afirmaron que el uso de la herramienta VigHub, apoya tanto en el análisis de datos como en la identificación de resultados útiles. Conclusiones: Contar con una herramienta que a partir de una sola consulta permite identificar parte del estado actual de una tecnología, podría ser una herramienta útil para académicos, desarrolladores y empresas, que ahorrarían recursos humanos, tiempo y posibles desarrollos repetidos---reutilización de código. La herramienta VigHub pretende apoyar en la construcción de un estado de arte. Sus resultados son complementarios al método tradicional. 
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-11-02 00:00:00
2024-04-09T20:21:54Z
dc.date.available.none.fl_str_mv 2021-11-02 00:00:00
2024-04-09T20:21:54Z
dc.date.issued.none.fl_str_mv 2021-11-02
dc.type.spa.fl_str_mv Artículo de revista
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D. Güemes-Peña, C. López-Nozal, R. Marticorena-Sánchez & J. Maudes-Raedo, “Emerging topics in mining software repositories: Machine learning in software repositories and datasets”, Prog Artif Intell, vol. 7, no. 3, pp. 237–247, Mar. 2018. https://doi.org/10.1007/s13748-018-0147-7
O. Meqdadi, N. Alhindawi, J. Alsakran, A. Saifan & H. Migdadi, “Mining software repositories for adaptive change commits using machine learning techniques,” Inf Softw Technol, vol. 109, pp. 80–91, May. 2019. https://doi.org/10.1016/j.infsof.2019.01.008
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M. A. Saied, A. Ouni, H. Sahraoui, R. G. Kula, K. Inoue & D. Lo, “Improving reusability of software libraries through usage pattern mining,” JSS, vol. 145, pp. 164–179, Nov. 2018. https://doi.org/10.1016/j.jss.2018.08.032
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spelling Hidalgo-Suarez, Carlos GiovannyBucheli-Guerrero , Victor AndresOrdoñez-Eraso , Hugo Armando2021-11-02 00:00:002024-04-09T20:21:54Z2021-11-02 00:00:002024-04-09T20:21:54Z2021-11-020122-6517https://hdl.handle.net/11323/12353https://doi.org/10.17981/ingecuc.18.1.2022.0710.17981/ingecuc.18.1.2022.072382-4700Introducción: Académicos, desarrolladores y empresas enfocadas en el desarrollo tecnológico, buscan conocer lo que ya existe y lo que aún falta en este campo. Una de las formas que utilizan, es realizar revisiones sobre fuentes bibliográficas (estado del arte). En este sentido, se desarrolló una herramienta que permite identificar el estado actual de una tecnología de forma semi-automática. Objetivo: Este artículo propone una herramienta que extrae información de repositorios alojados en GitHub. Analiza los datos utilizando técnicas computacionales y presenta los resultados a través de visualizaciones que identifican la evolución tecnológica del campo estudiado a través de los lenguajes de programación, principales, repositorios y organizaciones. Metodología: Se utiliza un modelo basado en Repositorios de Software de Minería (MSR), el cual integra una arquitectura basada en microservicios utilizando diferentes lenguajes de programación, lo que permitió la construcción de la herramienta VigHub. El modelo se centra en cuatro aspectos: selección de un tema tecnológico, extracción de la fuente de datos, análisis de la información mediante técnicas computacionales y finalmente, se muestran los resultados a través de visualizaciones. Resultados: Se dispuso la herramienta VigHub de manera online para realizar 3 casos de estudio. El primero en la academia, donde se identifico desde el año 2011 al 2021, las tecnologías, los lenguajes de programación, los usuarios y empresas interesadas en el desarrollo de VLE’s (Virtual Learning Environment). El segundo y tercero fueron ejecutados por empresas (ambiente industrial), que afirmaron que el uso de la herramienta VigHub, apoya tanto en el análisis de datos como en la identificación de resultados útiles. Conclusiones: Contar con una herramienta que a partir de una sola consulta permite identificar parte del estado actual de una tecnología, podría ser una herramienta útil para académicos, desarrolladores y empresas, que ahorrarían recursos humanos, tiempo y posibles desarrollos repetidos---reutilización de código. La herramienta VigHub pretende apoyar en la construcción de un estado de arte. Sus resultados son complementarios al método tradicional. Introduction: Academics, developers, and companies focused on technological development seek to know what exists and what is still missing in this field. One of the ways they use is the review of bibliographic sources (state-of-the art). In this sense, a tool was developed that allows the current state to be identified semi-automatically. Objective: This article proposes a tool that extracts information from repositories hosted on GitHub. It analyzes the data using computational techniques and presents the results through visualizations that identify the field's technological evolution studied through the most used programming languages, central repositories, and organizations. Method: A model based on Mining Software Repositories (MSR) is used, which integrates an architecture based on microservices, using different programming languages, which allowed the construction of the VigHub tool. The model focuses on four aspects: Selection of a topic, extraction of the data source, analysis of information using computational techniques, and finally, the results are communicated through visualizations. Results: The VigHub tool was available online to carry out 3 case studies. The first in the academy, where technologies, programming languages, users, and companies interested in developing VLE's (Virtual Learning Environment) were identified from 2011 to 2021. The second and third were carried out by companies (industrial environment), which stated that using the VigHub tool supports data analysis and valuable results identification. Conclusions: A tool that allows identifying a part of the current state of technology could be a helpful tool for academics, developers, and companies, saving human resources, time, and possible repeated developments---code reuse. The VigHub tool aims to support the construction of state-of-the-art. Its results are complementary to the traditional method.application/pdftext/htmltext/xmlengUniversidad de la CostaINGE CUC - 2021http://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistascientificas.cuc.edu.co/ingecuc/article/view/4065Mining Software RepositoriesTechnology ForecastingReview of technologiesTechnological mapsGitHubMinería de Repositorios de SoftwareVigilancia TecnológicaRevisión del estado de la técnicaMapas tecnológicosGitHubVIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de SoftwareVIGHUB: a Technology Forecasting Tool based on Mining Software RepositoriesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Inge CucA. 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Garriga, “Towards a taxonomy of microservices architectures,” presented at International Conference on Software Engineering and Formal Methods, SEFM, TLS, FR, 27-29 Jun. 2018. https://doi.org/10.1007/978-3-319-74781-1_15K. Bakshi, “Microservices-based software architecture and approaches,” presented at Aerospace Conference Proceedings, IEEE, Big Sky, MT, 4-11 Mar. 2017. https://doi.org/10.1109/AERO.2017.7943959Y. San Juan & F. Romero, “Management, extraction and storing sources for technological watch and competitive intelligence,” presented at VIII Congreso Internacional de Tecnologías y Contenidos Multimedia, CITCM, HAB, CU, 19-23 Mar. 2018.M. A. Saied, A. Ouni, H. Sahraoui, R. G. Kula, K. Inoue & D. Lo, “Improving reusability of software libraries through usage pattern mining,” JSS, vol. 145, pp. 164–179, Nov. 2018. https://doi.org/10.1016/j.jss.2018.08.032R. Dyer, H. A. Nguyen, H. Rajan & T. N. 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