Two sides of the same coin: Exploiting the impact of identifiers in neural code comprehension

• Main Authors: GAO, Shuzheng, GAO, Cuiyun, WANG, Chaozheng, SUN, Jun, LO, David, YU, Yue
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Code comprehension; Comprehension models; Counterfactuals; F1 scores; Misleading informations; Model prediction; Multitask learning; Neural code; Program semantics; Source codes; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/9270; https://ink.library.smu.edu.sg/context/sis_research/article/10270/viewcontent/TwoSidesCoin_2023_av.pdf
• Institution: Singapore Management University

Previous studies have demonstrated that neural code comprehension models are vulnerable to identifier naming. By renaming as few as one identifier in the source code, the models would output completely irrelevant results, indicating that identifiers can be misleading for model prediction. However, i...