2026-06-07T15:03:54Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112832026-01-27T01:05:46Zcom_10259_4219com_10259_5086com_10259_2604com_10259_5377col_10259_4220col_10259_5378

Alonso-Abad, Jesús M. 4c2d1e76-b81a-4d0e-b1c2-224d17e7ea8d 500 López Nozal, Carlos 322 600 0000-0001-8462-212X Maudes Raedo, Jesús M. 352 600 0000-0001-8808-412X Marticorena Sánchez, Raúl 338 600 0000-0002-2633-635X 2026-01-26T08:41:56Z 2026-01-26T08:41:56Z 2019-09 2192-6352 https://hdl.handle.net/10259/11283 10.1007/s13748-019-00182-2 2192-6360 Issue tracking systems are overall change-management tools in software development. The issue-solving life cycle is a complex socio-technical activity that requires team discussion and knowledge sharing between members. In that process, issue classification facilitates an understanding of issues and their analysis. Issue tracking systems permit the tagging of issues with default labels (e.g., bug, enhancement) or with customized team labels (e.g., test failures, performance). However, a current problem is that many issues in open-source projects remain unlabeled. The aim of this paper is to improve maintenance tasks in development teams, evaluating models that can suggest a label for an issue using its text comments. We analyze data on issues from several GitHub trending projects, first by extracting issue information and then by applying text mining classifiers (i.e., support vector machine and naive Bayes multinomial). The results suggest that very suitable classifiers may be obtained to label the issues or, at least, to suggest the most suitable candidate labels. We would like to thank the Ministerio de Economía y Competitividad of the Spanish Government for financing the Project TIN2015-67534-P (MINECO/FEDER, UE) and the Junta de Castilla y León for financing the Project BU085P17 (JCyL/FEDER, UE) both co-financed from European Union European Regional Development Fund (ERDF/FEDER) funds. We gratefully acknowledge the support of NVIDIA Corporation for the donation of TITAN Xp GPUs used for this research. application/pdf eng Springer Progress in Artificial Intelligence. 2019, V. 8, n. 3, p. 325–342 https://doi.org/10.1007/s13748-019-00182-2 Text classifier Experimentation in software engineering Issue tracker system Text mining Label prediction Ingeniería del software Inteligencia artificial Software engineering Artificial intelligence Label prediction on issue tracking systems using text mining info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/openAccess Progress in Artificial Intelligence 8 3 325 342 THUMBNAIL Alonso-pai_2019.pdf.jpg Alonso-pai_2019.pdf.jpg IM Thumbnail image/jpeg 3566 https://riubu.ubu.es/bitstream/10259/11283/3/Alonso-pai_2019.pdf.jpg 93018df5701f05a31bf9eb6f3718b533 MD5 3 LICENSE license.txt license.txt text/plain; charset=utf-8 999 https://riubu.ubu.es/bitstream/10259/11283/2/license.txt b295bcbce42e2caabeb0c623d3860c06 MD5 2 ORIGINAL Alonso-pai_2019.pdf Alonso-pai_2019.pdf application/pdf 480083 https://riubu.ubu.es/bitstream/10259/11283/1/Alonso-pai_2019.pdf 19d779605349086484da629f1bf8dd1d MD5 1 10259/11283 oai:riubu.ubu.es:10259/11283 2026-01-27 02:05:46.619 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es RWwgYXV0b3IgY29tbyDDum5pY28gdGl0dWxhciBkZSBsb3MgZGVyZWNob3MgZGUgcHJvcGllZGFkIGludGVsZWN0dWFsIGRlIGxhIG9icmEsIG8gZGlzcG9uaWVuZG8gZGUgbG9zIGRlYmlkb3MgcGVybWlzb3MgZGUgbG9zIG90cm9zIHRpdHVsYXJlcywgc2kgbG9zIGh1YmllcmEsIHkgZW4gdmlydHVkIGRlIGxvcyBkZXJlY2hvcyBxdWUgbGUgY29uZmllcmUgbGEgbGVnaXNsYWNpw7NuIHZpZ2VudGUgc29icmUgcHJvcGllZGFkIGludGVsZWN0dWFsIHkgZGVyZWNob3MgZGUgYXV0b3IsIA0KQVVUT1JJWkEgYSBsYSBVbml2ZXJzaWRhZCBkZSBCdXJnb3MgYSBkaWZ1bmRpciwgZGUgbWFuZXJhIGdyYXR1aXRhLCBlbCBjb250ZW5pZG8gZGUgbG9zIGFyY2hpdm9zIGRpZ2l0YWxlcyBxdWUgY29ycmVzcG9uZGVuIGFsIGRvY3VtZW50byBkZXNjcml0byBhbnRlcmlvcm1lbnRlLCBjb24gY2Fyw6FjdGVyIG5vIGV4Y2x1c2l2byB5IGRlIG1hbmVyYSBww7pibGljYSBlbiBhY2Nlc28gYWJpZXJ0byBhIHRyYXbDqXMgZGUgSW50ZXJuZXQsIHBhcmEgbG8gcXVlIGxhIEJpYmxpb3RlY2EgcHJvY2VkZXLDoSBhIGFyY2hpdmFybG9zIGVuIGVsIFJlcG9zaXRvcmlvIEluc3RpdHVjaW9uYWwuIEFzaW1pc21vIGF1dG9yaXphIGEgbGEgVW5pdmVyc2lkYWQgZGUgQnVyZ29zIGEgcmVhbGl6YXIgbGFzIHRyYW5zZm9ybWFjaW9uZXMgbmVjZXNhcmlhcyBkZSBmb3JtYXRvLCBubyBkZSBjb250ZW5pZG8sIHBhcmEgZ2FyYW50aXphciBsYSBwcmVzZXJ2YWNpw7NuIHkgZWwgYWNjZXNvIGVuIGVsIGZ1dHVyby4NCg0KRWwgYXV0b3IgZGlzcG9uZSwgZW4gdG9kbyBjYXNvLCBkZWwgZGVyZWNobyBhIHJldm9jYXIgZXN0YSBhdXRvcml6YWNpw7NuLg0KDQpMYSBjZXNpw7NuIGRlIGRlcmVjaG9zIGRlIGVzdGEgb2JyYSBzZSBlbmN1ZW50cmEgc3VqZXRhIGEgbGEgbGVnaXNsYWNpw7NuIHZpZ2VudGUgc29icmUgcHJvcGllZGFkIGludGVsZWN0dWFsIHkgZGVyZWNob3MgZGUgYXV0b3Iu