dc.contributor.author | Aguilera, Cristina |
dc.contributor.author | Albors Zumel, Laia |
dc.contributor.author | Antoñanzas, Jesús M. |
dc.contributor.author | Lenarduzzi, Valentina |
dc.contributor.author | Martínez Fernández, Silverio Juan |
dc.contributor.author | Rabanaque Rodríguez, Sonia |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2022-05-02T16:47:30Z |
dc.date.available | 2022-05-02T16:47:30Z |
dc.date.issued | 2021 |
dc.identifier.citation | Aguilera, C. [et al.]. A preliminary investigation of developer profiles based on their activities and code quality: who does what? A: IEEE International Conference on Software Quality, Reliability and Security Companion. "2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C)". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 938-945. ISBN 9781665478373. DOI 10.1109/QRS54544.2021.00103. |
dc.identifier.isbn | 9781665478373 |
dc.identifier.uri | http://hdl.handle.net/2117/366672 |
dc.description.abstract | Developers work on different tasks in different conditions based on individual technical skills and personal habits. Identifying developer groups by mining their repositories is key for various tasks ranging from understanding developers types in open source projects, to help project managers concerned with the team allocation and coordination of human resources in companies. We aimed at identifying distinct groups of developer profiles based on well defined characteristics and at characterizing the most common quality issue types introduced by each profile in their code. We considered 77,932 commits of 33 open source Java projects, clustering their 2460 developers using dimensionality reduction techniques and applying the k-means algorithm. We identified five profiles among 2460 developers based on project experience, developer productivity and the common quality issues they introduce in the code. Results can be used by developer teams to detect and cope with harmful practices, in order to be more efficient by reducing the number of bugs they produce, looking for adequate training options, and balancing their teams. |
dc.description.sponsorship | The research presented in this paper has been developed in the context of the TAED2 course at the GCED@FIB.
This work has been partially funded by the “Beatriz Galindo” Spanish Program BEAGAL18/00064 and by the DOGO4ML
Spanish research project (ref. PID2020-117191RB-I00) |
dc.format.extent | 8 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject.lcsh | Machine learning |
dc.subject.lcsh | Software engineering |
dc.subject.other | Machine learning |
dc.subject.other | Developer characterisation |
dc.subject.other | SonarQube |
dc.subject.other | Code quality |
dc.subject.other | Software engineering |
dc.title | A preliminary investigation of developer profiles based on their activities and code quality: who does what? |
dc.type | Conference lecture |
dc.subject.lemac | Aprenentatge automàtic |
dc.subject.lemac | Enginyeria de programari |
dc.contributor.group | Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
dc.identifier.doi | 10.1109/QRS54544.2021.00103 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9724936 |
dc.rights.access | Open Access |
local.identifier.drac | 32777955 |
dc.description.version | Postprint (author's final draft) |
local.citation.author | Aguilera, C.; Albors Zumel, L.; Antoñanzas, J.; Lenarduzzi, V.; Martínez-Fernández, S.; Rabanaque, S. |
local.citation.contributor | IEEE International Conference on Software Quality, Reliability and Security Companion |
local.citation.publicationName | 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C) |
local.citation.startingPage | 938 |
local.citation.endingPage | 945 |