TY - GEN
T1 - Software Defect Prediction for Specific Defect Types based on Augmented Code Graph Representation
AU - Xu, Jiaxi
AU - Ai, Jun
AU - Shi, Tao
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In a software life cycle, improving quality and identifying and repairing defects has become an important research topic. Previous studies have proposed defect prediction based on artificial measurement features, a method whose quality is unfortunately difficult to guarantee. On the other hand, many current studies have attempted to predict all types of defects using a single model, which is difficult to achieve. In this paper, Augmented-CPG, a new code graph representation, is proposed. Based on this representation, a defect region candidate extraction method related to the defect type is proposed. Graphic neural networks are introduced to learn defect features. We carried out experiments on three different types of defects, and the results show that our method can effectively predict specific types of defects.
AB - In a software life cycle, improving quality and identifying and repairing defects has become an important research topic. Previous studies have proposed defect prediction based on artificial measurement features, a method whose quality is unfortunately difficult to guarantee. On the other hand, many current studies have attempted to predict all types of defects using a single model, which is difficult to achieve. In this paper, Augmented-CPG, a new code graph representation, is proposed. Based on this representation, a defect region candidate extraction method related to the defect type is proposed. Graphic neural networks are introduced to learn defect features. We carried out experiments on three different types of defects, and the results show that our method can effectively predict specific types of defects.
KW - Defect prediction
KW - code representation
KW - defect types
KW - graph neural networks
UR - https://www.scopus.com/pages/publications/85123502800
U2 - 10.1109/DSA52907.2021.00097
DO - 10.1109/DSA52907.2021.00097
M3 - 会议稿件
AN - SCOPUS:85123502800
T3 - Proceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021
SP - 669
EP - 678
BT - Proceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Dependable Systems and Their Applications, DSA 2021
Y2 - 11 September 2021 through 12 September 2021
ER -