VIGHUB: a technology forecasting tool based on mining software repositories
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 st...
- Autores:
-
Hidalgo-Suarez, Carlos Giovanny
Bucheli-Guerrero, Víctor Andrés
Ordoñez-Eraso, Hugo Armando
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9866
- Acceso en línea:
- https://hdl.handle.net/11323/9866
https://repositorio.cuc.edu.co/
- Palabra clave:
- Mining software repositories
Technology forecasting
State-of-the technique
GitHub
Technological maps
Minería de repositorios de software
Vigilancia tecnológica
Estado de la técnica
Mapas tecnológicos
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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VIGHUB: a technology forecasting tool based on mining software repositories |
| dc.title.translated.none.fl_str_mv |
VIGHUB: una herramienta de pronóstico tecnológico basada en minería de repositorios de software |
| title |
VIGHUB: a technology forecasting tool based on mining software repositories |
| spellingShingle |
VIGHUB: a technology forecasting tool based on mining software repositories Mining software repositories Technology forecasting State-of-the technique GitHub Technological maps Minería de repositorios de software Vigilancia tecnológica Estado de la técnica Mapas tecnológicos |
| title_short |
VIGHUB: a technology forecasting tool based on mining software repositories |
| title_full |
VIGHUB: a technology forecasting tool based on mining software repositories |
| title_fullStr |
VIGHUB: a technology forecasting tool based on mining software repositories |
| title_full_unstemmed |
VIGHUB: a technology forecasting tool based on mining software repositories |
| title_sort |
VIGHUB: a technology forecasting tool based on mining software repositories |
| dc.creator.fl_str_mv |
Hidalgo-Suarez, Carlos Giovanny Bucheli-Guerrero, Víctor Andrés Ordoñez-Eraso, Hugo Armando |
| dc.contributor.author.none.fl_str_mv |
Hidalgo-Suarez, Carlos Giovanny Bucheli-Guerrero, Víctor Andrés Ordoñez-Eraso, Hugo Armando |
| dc.subject.proposal.eng.fl_str_mv |
Mining software repositories Technology forecasting State-of-the technique GitHub Technological maps |
| topic |
Mining software repositories Technology forecasting State-of-the technique GitHub Technological maps Minería de repositorios de software Vigilancia tecnológica Estado de la técnica Mapas tecnológicos |
| dc.subject.proposal.spa.fl_str_mv |
Minería de repositorios de software Vigilancia tecnológica Estado de la técnica Mapas tecnológicos |
| description |
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. |
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2022 |
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2022 |
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2023-02-06T15:52:17Z |
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2023-02-06T15:52:17Z |
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Artículo de revista |
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C. Hidalgo-Suarez, V. Bucheli-Guerrero & H. Ordoñez-Eraso, “VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software”, INGE CUC, vol. 18, no. 1, pp. 83–94, 2022. DOI: http://doi.org/10.17981/ingecuc.18.1.2022.07 |
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0122-6517 |
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https://hdl.handle.net/11323/9866 |
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10.17981/ingecuc.18.1.2022.07 |
| dc.identifier.eissn.spa.fl_str_mv |
2382-4700 |
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Corporación Universidad de la Costa |
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REDICUC – Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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C. Hidalgo-Suarez, V. Bucheli-Guerrero & H. Ordoñez-Eraso, “VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software”, INGE CUC, vol. 18, no. 1, pp. 83–94, 2022. DOI: http://doi.org/10.17981/ingecuc.18.1.2022.07 0122-6517 10.17981/ingecuc.18.1.2022.07 2382-4700 Corporación Universidad de la Costa REDICUC – Repositorio CUC |
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https://hdl.handle.net/11323/9866 https://repositorio.cuc.edu.co/ |
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eng |
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eng |
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INGE CUC |
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[1] A. Peralta & F. P. Romero, “Decision making from knowledge obtained after previous behavior analysis. Practical implementation to project management of software development,” Rev Cintex, vol. 20, no. 2, pp. 97–111, Nov. 2015. https://revistas.pascualbravo.edu.co/index.php/cintex/article/view/26 [2] 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 [3] 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 [4] M. 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Bacchelli, “PyDriller: Python framework for mining software repositories,” presented at 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE, NYC, NY, USA, 4-9 Nov. 2018. https://doi.org/10.1145/3236024.3264598 [13] S. Dueñas, V. Cosentino, G. Robles & J. M. Gonzalez-Barahona, “Perceval: software project data at your will,” presented at 40th International Conference on Software Engineering: Companion, ICSE-Companion, GBG, SE, 27 May.-3 Jun. 018. https://ieeexplore.ieee.org/document/8449430 [14] J. J. Ramírez-Echeverry, F. Restrepo-Calle & F. A. González, “Uncode: interactive system for learning and automatic evaluation of computer programming skills”, presented at 10th International Conference on Education and New Learning Technologies, EDULEARN, PMI, ES, 2-4 Jul. 2018. https://doi. org/10.21125/edulearn.2018.1632 [15] E. Ortíz, “La evaluación del impacto científico en las investigaciones educativas a través de un estudio de caso,” REDIE, vol. 17, no. 2, pp. 89–100, May. 2015. https://www.scienceopen.com/document?vid=0de24d4cb9e3-4739-b394-346f7480b4fe [16] A. Berges-García, J. M. Meneses-Chaus & J. F. Martínez-Ortega, “Methodology for evaluating functions and products for technology watch and competitive intelligence (TW/CI) and their implementation through web,” PEI, vol. 25, no. 1, pp. 103–113, Jan. 2016. https://doi.org/10.3145/epi.2016.ene.10 [17] SpaCy, “Industrial-Strength Natural Language Processing in Python,” Accessed: Oct. 18, 2019. [Online]. Available: https://spacy.io/ [18] Google Developers. “Google Charts.” Accessed: 2018. [Online]. Available: https://developers.google.com/ chart [19] P. T. Goeser, F. G. Hamza-Lup, W. M. Johnson & D. Scharfer, “VIEW: A Virtual Interactive Webbased Learning Environment for Engineering,” AEEE, vol. 2, no. 3, pp. 1–24, Dec. 2011. https://doi. org/10.48550/arXiv.1811.07463 [20] WISE-Community, “WISE VLE,” Feb. 25, 2015. [Online]. Available: https://github.com/WISE-Community/WISE-VLE--Deprecated-- [21] F. Supriadi, M. Agreindra Helmiawan, Y. Y. Sofiyan & A. Guntara, “A Model of Virtual Learning Environments Using Micro-Lecture, MOODLE, and SLOODLE,” presented at 8th International Conference on Cyber and IT Service Management, CITSM, PGX, ID, 23-24 Dec. 020. https://doi.org/10.1109/CITSM50537.2020.9268785 [22] Knowm, “Proprioceptron,” Oct. 27, 2012. [Online]. Available: https://github.com/knowm/Proprioceptron [23] Yjwong, “com.nuscomputing.ivlelapi,” Aug. 14, 2012. [Online]. Available: https://github.com/yjwong/com.nuscomputing.ivlelapi [24] 40thieves, “WikiVLE,” Jun. 23, 2012. [Online]. Available: https://github.com/40thieves/WikiVLE [25] Jbittencourt, “massinha,” Jul. 5, 2012. [Online]. Available: https://github.com/jbittencourt/massinha [26] Conel, “moodle-1.9,” Aug. 20, 2012. [Online]. Available: https://github.com/conel/moodle-1.9 [27] Elkuku, “JDevAndLearn,” Jul. 28, 2012. [Online]. Available: https://github.com/elkuku/JDevAndLearn [28] Champiewebfolio, “CloudPod,” Jan. 6, 2013. [Online]. Available: https://github.com/champiewebfolio/CloudPod [29] RheoDesign, “AAVS-Beijing,” Oct. 23, 2013. [Online]. Available: https://github.com/RheoDesign/AAVSBeijing [30] Roxolan, “vlemean,” Aug. 11, 2015. [Online]. Available: https://github.com/roxolan/vlemean [31] luistp001, “LT-Autograder,” Sep. 16, 2012. [Online]. Available: https://github.com/luistp001/LT-Autograder [32] StephenBergeron, “RubySoup,” Apr. 1, 2014. [Online]. Available: https://github.com/StephenBergeron/ RubySoup [33] Deepapanwar, “vle,” Jun. 16, 2015. [Online]. Available: https://github.com/deepapanwar/vle [34] Soyjun, “Implement-ODR-protocol,” Apr. 10, 2015. [Online]. Available: https://github.com/SOYJUN/Implement-ODR-protocol [35] Brukmoon, “eduqo-vle,” Apr. 23, 2015. [Online]. Available: https://github.com/Brukmoon/eduqo-vle [36] Sykonba, “PeerReviewSystem,” Nov. 2, 2015. [Online]. Available: https://github.com/Sykonba/PeerReviewSystem [37] DavidStCox, “nlp-vle,” Apr. 10, 2017. [Online]. Available: https://github.com/DavidStCox/nlp-vle [38] Lumeng, “univ-washington-machine-learning-python-virtualenv,” Dec. 3, 2017. [Online]. Available: https://github.com/lumeng/univ-washington-machine-learning-python-virtualenv [39] Blosm-org, “blosm-core,” Sep. 30, 2017. [Online]. Available: https://github.com/blosm-org/blosm-core [40] Cvgokhale, “Course-Completion-Rate-Prediction,” Jul. 16, 2017. [Online]. Available: https://github.com/ cvgokhale/Course-Completion-Rate-Prediction [41] Victor-iyiola, “navigating-a-virtual-world-using-dynamic-programming,” Nov. 26, 2017. [Online]. Available: https://github.com/victor-iyiola/navigating-a-virtual-world-using-dynamic-programming [42] Charvi5, “VirtualLearning-Analysis-Classification,” Apr. 4, 2018. [Online]. Available: https://github.com/charvi5/VirtualLearning-Analysis-Classification [43] Viniciusvec, “hackops,” Mar. 2, 2018. [Online]. Available: https://github.com/viniciusvec/hackops [44] Fernando24164, “breakfast_docker,” Feb. 2, 2018. [Online]. Available: https://github.com/fernando24164/ breakfast_docker [45] pupilfirst, “pupilfirst,” Aug. 2, 2021. [Online]. Available: https://github.com/pupilfirst/pupilfirst [46] tparisi, “LearningVirtualReality,” Mar. 4, 2016. [Online]. Available: https://github.com/tparisi/LearningVirtualReality [47] Aayushi15061997, “Reinforcement_Learning_ThompsonSampling,” Jan 29, 2018. [Online]. Available: https://github.com/aayushi15061997/Reinforcement_Learning_ThompsonSampling [48] The-Dank-Network, “TDVLE-API,” Mar. 23, 2019. [Online]. Available: https://github.com/The-DankNetwork/TDVLE-API [49] C. G. Hidalgo, V. A. Bucheli, F. Restrepo-Calle & F. A. González, “A strategy based on technological maps for the identification of the state-of-the-art techniques in software development projects: Virtual judge projects as a case study,” in Communications in Computer and Information Science, C. J. Serrano & J. Martínez-Santos, Cham, CH: Springer, 2018, vol. 885, pp. 338–354. https://doi.org/10.1007/978-3- 319-98998-3_27 |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)Derechos de autor 2021 INGE CUChttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Hidalgo-Suarez, Carlos GiovannyBucheli-Guerrero, Víctor AndrésOrdoñez-Eraso, Hugo Armando2023-02-06T15:52:17Z2023-02-06T15:52:17Z2022C. Hidalgo-Suarez, V. Bucheli-Guerrero & H. Ordoñez-Eraso, “VIGHUB: una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software”, INGE CUC, vol. 18, no. 1, pp. 83–94, 2022. DOI: http://doi.org/10.17981/ingecuc.18.1.2022.070122-6517https://hdl.handle.net/11323/986610.17981/ingecuc.18.1.2022.072382-4700Corporación Universidad de la CostaREDICUC – Repositorio CUChttps://repositorio.cuc.edu.co/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.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.12 páginasapplication/pdfengCorporación Universidad de la CostaColombiahttps://revistascientificas.cuc.edu.co/ingecuc/article/view/4065VIGHUB: a technology forecasting tool based on mining software repositoriesVIGHUB: una herramienta de pronóstico tecnológico basada en minería de repositorios de softwareArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85INGE CUC[1] A. 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Martínez-Santos, Cham, CH: Springer, 2018, vol. 885, pp. 338–354. https://doi.org/10.1007/978-3- 319-98998-3_279483118Mining software repositoriesTechnology forecastingState-of-the techniqueGitHubTechnological mapsMinería de repositorios de softwareVigilancia tecnológicaEstado de la técnicaMapas tecnológicosPublicationORIGINALVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdfVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdfArtículoapplication/pdf689621https://repositorio.cuc.edu.co/bitstreams/60f0e6db-d9a0-4fb1-807f-ae2c4c6a046e/downloada9e539101916525d0e1f6a4346f62b68MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.cuc.edu.co/bitstreams/2f182390-5567-48db-b505-8c530ad15dcc/download2f9959eaf5b71fae44bbf9ec84150c7aMD52TEXTVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdf.txtVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdf.txtExtracted texttext/plain44094https://repositorio.cuc.edu.co/bitstreams/30c9510b-9a59-4d9d-9298-934ec3b247b0/downloadd095b1ab6749f0cffd9c4a3f9ce1718fMD53THUMBNAILVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdf.jpgVIGHUB. una Herramienta de Pronóstico Tecnológico basada en Minería de Repositorios de Software.pdf.jpgGenerated Thumbnailimage/jpeg13338https://repositorio.cuc.edu.co/bitstreams/424ba498-abb8-483d-80c4-4fa311f1c7c6/downloadd70e1839005c41b270f861d52ecced2eMD5411323/9866oai:repositorio.cuc.edu.co:11323/98662024-09-17 10:18:38.566https://creativecommons.org/licenses/by-nc-nd/4.0/Derechos de autor 2021 INGE CUCopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa 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ada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
 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