Resource Classification from Version Control System Logs

Kushal Agrawal, Michael Aschauer, Thomas Thonhofer, Saimir Bala, Andreas Solti, Nico Tomsich

Publikation: Beitrag in Buch/KonferenzbandBeitrag in Konferenzband

Abstract

Collaboration in business processes and projects requires a division of responsibilities among the participants. Version control systems allow us to collect profiles of the participants that hint at participants' roles in the collaborative work. The goal of this paper is to automatically classify participants into the roles they fulfill in the collaboration. Two approaches are proposed and compared in this paper. The first approach finds classes of users by applying k-means clustering to users based on attributes calculated for them. The classes identified by the clustering are then used to build a decision tree classification model. The second approach classifies individual commits based on commit messages and file types. The distribution of commit types is used for creating a decision tree classification model. The two approaches are implemented and tested against three real datasets, one from academia and two from industry. Our classification covers 86% percent of the total commits. The results are evaluated with actual role information that was manually collected from the teams responsible for the analyzed repositories.
OriginalspracheEnglisch
Titel des Sammelwerks20th IEEE International Enterprise Distributed Object Computing Workshop, EDOC Workshops 2016, Vienna, Austria, September 5-9, 2016
Herausgeber*innen Remco Dijkman, Luís Ferreira Pires, Stefanie Rinderle-Ma
ErscheinungsortVienna, Austria
VerlagIEEE Computer Society Press
Seiten1 - 10
ISBN (Print)978-1-4673-9933-3
DOIs
PublikationsstatusVeröffentlicht - 2016

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

  • 102 not use (Altbestand)
  • 502 not use (Altbestand)

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