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1 Ergebnisse
1
Determining the Most Significant Metadata Features to Indic..:
, In:
2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)
,
Dey, Rupam Kumar
;
Khojandi, Anahita
;
Perumalla, Kalyan
- p. 258-265 , 2023
Link:
https://doi.org/10.1109/SERA57763.2023.10197721
RT T1 <cTitle>2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)</cTitle>: T1 <Title>Determining the Most Significant Metadata Features to Indicate Defective Software Commits</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10197721&Exemplar=1&LAN=DE A1 Dey, Rupam Kumar A1 Khojandi, Anahita A1 Perumalla, Kalyan YR 2023 SN 2770-8209 K1 Computer bugs K1 Machine learning K1 Forestry K1 Predictive models K1 Metadata K1 Feature extraction K1 Software K1 Bugs K1 Software Development Life Cycle K1 Feature Selection K1 Random Forest Model K1 Wrapper Method SP 258 OP 265 LK http://dx.doi.org/https://doi.org/10.1109/SERA57763.2023.10197721 DO https://doi.org/10.1109/SERA57763.2023.10197721 SF ELIB - SuUB Bremen
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