scholarly journals An empirical study on the effectiveness of data resampling approaches for cross‐project software defect prediction

IET Software ◽  
2021 ◽  
Author(s):  
Kwabena Ebo Bennin ◽  
Amjed Tahir ◽  
Stephen G. MacDonell ◽  
Jürgen Börstler
Keyword(s):  
Empirical Study ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Cross Project

scholarly journals An Empirical Study on Software Defect Prediction Using CodeBERT Model

2021 ◽  
Vol 11 (11) ◽  
pp. 4793
Author(s):  
Cong Pan ◽  
Minyan Lu ◽  
Biao Xu
Keyword(s):  
Deep Learning ◽  
Software Engineering ◽  
Empirical Study ◽  
Empirical Studies ◽  
Language Model ◽  
Prediction Performance ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Cross Project

Deep learning-based software defect prediction has been popular these days. Recently, the publishing of the CodeBERT model has made it possible to perform many software engineering tasks. We propose various CodeBERT models targeting software defect prediction, including CodeBERT-NT, CodeBERT-PS, CodeBERT-PK, and CodeBERT-PT. We perform empirical studies using such models in cross-version and cross-project software defect prediction to investigate if using a neural language model like CodeBERT could improve prediction performance. We also investigate the effects of different prediction patterns in software defect prediction using CodeBERT models. The empirical results are further discussed.

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