An algorithmic approach to missing data problem in modeling human aspects in software development
Gül Çalıklı, Ayşe Bener · 2013
Background: In our previous research, we built defect prediction models by using confirmation bias metrics. Due to confirmation bias developers tend to perform unit tests to make their programs run rather than breaking their code. This, in turn, leads to an increase in defect density. The performance of prediction model that is built using confirmation bias was as good as the models that were built with static code or churn metrics.