Boosting Just-in-Time Defect Prediction with Specific Features of C/C plus plus Programming Languages in Code Changes

Just-in-time (JIT) defect prediction can identify changes as defect-inducing ones or clean ones and many approaches are proposed based on several programming languageindependent change-level features. However, different programming languages have different characteristics and consequently may affect the quality of software projects. Meanwhile, the C programming language, one of the most popular ones, is widely used to develop foundation applications (i.e., operating system, database, compiler, etc.) in IT companies and its changelevel characteristics on project quality have not been fully investigated. Additionally, whether open-source C projects have similar important features to commercial projects has not been studied much. To address the aforementioned limitations, in this paper, we investigate the impacts of programming language-specific features on the state-of-the-art JIT defect identification approach in an industrial setting. We collect and label the top-10 most starred C projects (i.e., 329,021 commits) on GitHub and 8 C projects in an ICT company (i.e., 12,983 commits). We also propose nine C-specific change-level features and focus our investigations on both open-source C projects on GitHub and C projects at the ICT company considering three aspects: (1) The effectiveness of C-specific change-level features in improving the performance of identification of defect-inducing changes, (2) The importance of features in the identification of defect-inducing changes between open-source C projects and commercial C projects, and (3) The effectiveness of combining language-independent features and Cspecific features in a real-life setting at the ICT company.