dc.contributorUniversidade Tecnológica Federal do Paraná (UTFPR)
dc.contributorUniversidade Federal da Bahia (UFBA)
dc.contributorUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-28T19:01:26Z
dc.date.accessioned2022-12-20T00:59:00Z
dc.date.available2022-04-28T19:01:26Z
dc.date.available2022-12-20T00:59:00Z
dc.date.created2022-04-28T19:01:26Z
dc.date.issued2015-06-01
dc.identifierIEEE Latin America Transactions, v. 13, n. 6, p. 1979-1988, 2015.
dc.identifier1548-0992
dc.identifierhttp://hdl.handle.net/11449/220416
dc.identifier10.1109/TLA.2015.7164225
dc.identifier2-s2.0-84938401083
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5400545
dc.description.abstractDevelopers have contributed to open-source projects by forking the code and submitting pull requests. Once a pull request is submitted, interested parties can review the set of changes, discuss potential modifications, and even push additional commits if necessary. Mining artifacts that were committed together during history of pull-requests makes it possible to infer change couplings among these artifacts. Supported by the Conway's Law, whom states that organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations, we hypothesize that social network analysis (SNA) is able to identify strong and weak change dependencies. In this paper, we used statistical models relying on centrality, ego, and structural holes metrics computed from communication networks to predict co-changes among files included in pull requests submitted to the Ruby on Rails project. To the best of our knowledge, this is the first study to employ SNA metrics to predict change dependencies from Github projects
dc.languagepor
dc.relationIEEE Latin America Transactions
dc.sourceScopus
dc.subjectchange coupling
dc.subjectcommunication network
dc.subjectConways law
dc.subjectsocial network analysis
dc.subjectstructural holes metrics
dc.titleDo historical metrics and developers communication aid to predict change couplings?
dc.typeArtículos de revistas


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