Boosting Just-in-Time Defect Prediction with Specific Features of C/C++ 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 language-independent change-level features. However, different programming languages have different characteristics and consequently may affec...
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| Veröffentlicht in: | Proceedings (IEEE/ACM International Conference on Mining Software Repositories. Online) S. 472 - 484 |
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IEEE
01.05.2023
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| ISSN: | 2574-3864 |
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| Abstract | 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 language-independent 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 change-level 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 C-specific features in a real-life setting at the ICT company. |
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| AbstractList | 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 language-independent 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 change-level 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 C-specific features in a real-life setting at the ICT company. |
| Author | Ni, Chao Lo, David Yang, Kaiwen Xu, Xiaodan |
| Author_xml | – sequence: 1 givenname: Chao surname: Ni fullname: Ni, Chao email: chaoni@zju.edu.cn organization: Zhejiang University,China – sequence: 2 givenname: Xiaodan surname: Xu fullname: Xu, Xiaodan email: xiaodanxu@zju.edu.cn organization: Zhejiang University,China – sequence: 3 givenname: Kaiwen surname: Yang fullname: Yang, Kaiwen email: kwyang@zju.edu.cn organization: Zhejiang University,China – sequence: 4 givenname: David surname: Lo fullname: Lo, David email: davidlo@smu.edu.sg organization: Singapore Management University,Singapore |
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| Snippet | 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... |
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| SubjectTerms | C/C++ programming language Just-in-Time Supervised Methods |
| Title | Boosting Just-in-Time Defect Prediction with Specific Features of C/C++ Programming Languages in Code Changes |
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