1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.SE2025
On the calibration of Just-in-time Defect Prediction
Xhulja Shahini, Jone Bartel, Klaus Pohl
Just in time defect prediction (JIT DP) leverages ML to identify defect-prone code commits, enabling quality assurance (QA) teams to allocate resources more efficiently by focusing…
cs.SE2023★ 1 cited
Variance of ML-based software fault predictors: are we really improving fault prediction?
Xhulja Shahini, Domenic Bubel, Andreas Metzger
Software quality assurance activities become increasingly difficult as software systems become more and more complex and continuously grow in size. Moreover, testing becomes even m…