Code Smell Detection using Features from Version History
| dc.contributor.author | Engeln, Ulrike | |
| dc.contributor.editor | Herrmann, Andrea | |
| dc.date.accessioned | 2024-02-22T10:39:10Z | |
| dc.date.available | 2024-02-22T10:39:10Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Code smells are indicators for bad quality of source code. A well suited approach for the development of a smell detector are machine learning techniques that learn based on features, i.e., measurable properties of the software under investigation, e.g., code metrics. One major objective of our machine learning approach is to decide how to express information from the version history by features. we introduce a method to draw historical features that improve smell detection. | en |
| dc.identifier.issn | 0720-8928 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43665 | |
| dc.language.iso | en | |
| dc.pubPlace | Bonn | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Softwaretechnik-Trends Band 43, Heft 2 | |
| dc.relation.ispartofseries | Softwaretechnik-Trends | |
| dc.subject | code smell | |
| dc.subject | detection | |
| dc.subject | version history | |
| dc.subject | machine learning | |
| dc.subject | code metrics | |
| dc.title | Code Smell Detection using Features from Version History | en |
| dc.type | Text/Conference Paper | |
| mci.conference.date | 44993 | |
| mci.conference.location | Bad Honnef, Germany | |
| mci.conference.sessiontitle | 25. Workshop Software-Reengineering und -Evolution der GI-Fachgruppe Software Reengineering (SRE) | |
| mci.reference.pages | 38-39 |
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