Continuous Software Bug Prediction

Abstract

Background: Many software bug prediction models have been proposed and evaluated on a set of well-known benchmark datasets. We conducted pilot studies on the widely used benchmark datasets and observed common issues among them. Specifically, most of existing benchmark datasets consist of randomly selected historical versions of software projects, which poses non-trivial threats to the validity of existing bug prediction studies since the real-world software projects often evolve continuously. Yet how to conduct software bug prediction in the real-world continuous software development scenarios is not well studied.