Mining Java Packages for Developer Profiles: An Exploratory Study
| dc.contributor.author | Ramadani, Jasmin | |
| dc.contributor.author | Wagner, Stefan | |
| dc.contributor.editor | Mitschang, Bernhard | |
| dc.contributor.editor | Nicklas, Daniela | |
| dc.contributor.editor | Leymann, Frank | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Herschel, Melanie | |
| dc.contributor.editor | Teubner, Jens | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Kopp, Oliver | |
| dc.contributor.editor | Wieland, Matthias | |
| dc.date.accessioned | 2017-06-21T11:24:37Z | |
| dc.date.available | 2017-06-21T11:24:37Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | Not all developers have the same degree of knowledge of all parts of a software system. For allocating new task expertise, it would be interesting to have different developer profiles explicit. The state of the practice is to find out manually who might be most experienced in a certain area. A clear understanding how to automate this analysis is missing. Our goal is to explore to what degree the analysis of couplings of packages can be useful for this automation. Our analysis approach uses the idea that packages reflect the organization of the source code into basic functionalities. We use data mining on the version history to identify the sets of the packages that were most frequently changed together in different occasions. We present a case study where we analyze three open-source software systems to define developer expertise profiles based on the aggregation of the packages. Our results identify different developer profiles. They can be especially useful in analyzing projects with a larger number of developers saving time and effort by limiting the data sets to be investigated to find relevant software changes. | en |
| dc.identifier.isbn | 978-3-88579-660-2 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-266 | |
| dc.subject | Version history | |
| dc.subject | Packages | |
| dc.subject | Developers expertise | |
| dc.title | Mining Java Packages for Developer Profiles: An Exploratory Study | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 154 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 143 | |
| gi.conference.date | 6.-10. März 2017 | |
| gi.conference.location | Stuttgart | |
| gi.conference.sessiontitle | Workshop on Industrial Applications of Artificial Intelligence (IAAI’17) |
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