15 citations · 36 across the 4 of their papers we have counts for
5 papers
On the Use of Deep Learning in Software Defect Prediction
Görkem Giray, Kwabena Ebo Bennin, Ömer Köksal +2
Context: Automated software defect prediction (SDP) methods are increasingly applied, often with the use of machine learning (ML) techniques. Yet, the existing ML-based approaches…
Does class size matter? An in-depth assessment of the effect of class size in software defect prediction
Amjed Tahir, Kwabena E. Bennin, Xun Xiao +1
In the past 20 years, defect prediction studies have generally acknowledged the effect of class size on software prediction performance. To quantify the relationship between object…
Investigating the Significance of Bellwether Effect to Improve Software Effort Estimation
Solomon Mensah, Jacky Keung, Stephen G. MacDonell +2
Bellwether effect refers to the existence of exemplary projects (called the Bellwether) within a historical dataset to be used for improved prediction performance. Recent studies h…
Investigating the Significance of the Bellwether Effect to Improve Software Effort Prediction: Further Empirical Study
Solomon Mensah, Jacky Keung, Stephen G. MacDonell +2
Context: In addressing how best to estimate how much effort is required to develop software, a recent study found that using exemplary and recently completed projects [forming Bell…
Revisiting the size effect in software fault prediction models
Amjed Tahir, Kwabena E. Bennin, Stephen G. MacDonell +1
BACKGROUND: In object oriented (OO) software systems, class size has been acknowledged as having an indirect effect on the relationship between certain artifact characteristics, ca…