3 papers
cs.SE2026
An Audit of Machine Learning Experiments on Software Defect Prediction
Giuseppe Destefanis, Leila Yousefi, Martin Shepperd +4
Background: Machine learning algorithms are widely used to predict defect prone software components. In this literature, computational experiments are the main means of evaluation,…
cs.LG2019
The Prevalence of Errors in Machine Learning Experiments
Martin Shepperd, Yuchen Guo, Ning Li +7
Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct rel…
cs.SE2019
On the Relationship Between Coupling and Refactoring: An Empirical Viewpoint
Steve Counsell, Mahir Arzoky, Giuseppe Destefanis +1
[Background] Refactoring has matured over the past twenty years to become part of a developer's toolkit. However, many fundamental research questions still remain largely unexplore…