Rotation Forest in Software Defect Prediction (CROSBI ID 625370)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Mauša, Goran ; Bogunović, Nikola ; Galinac Grbac, Tihana ; Dalbelo Bašić, Bojana
engleski
Rotation Forest in Software Defect Prediction
Software Defect Prediction (SDP) deals with localization of potentially faulty areas of the source code. Classification models are the main tool for performing the prediction and the search for a model of utmost performance is an ongoing activity. This paper explores the performance of Rotation Forest classification al gorithm in the SDP problem domain. Rotation Forest is a novel algorithm that exhibited excellent performance in several studies. However, it was not systematically used in the SDP. Furthermore, it is very important to perform the case studies in various contexts. This study uses 5 subsequent releases of Eclipse JDT as the objects of the analysis. The performance evaluation is based on comparison with two other, known classification models that exhibited very good performance so far. The results of our case study concur with other studies that recognize the Rotation forest to be the state of the art classification algorithm
Rotation Forest; Random Forest; Logistic Regression; Software Defect Prediction
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Podaci o prilogu
35-43.
2015.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of SQAMIA 2015
Budimac, Zoran ; Heričko, Marjan
Maribor:
978-961-248-485-9
Podaci o skupu
Fourth Workshop on Software Quality Analysis, Monitoring, Improvement and Applications
predavanje
08.06.2015-10.06.2015
Maribor, Slovenija