Classifying source code: How far can compressor-based classifiers go?

• Main Author: YANG, Zhou
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Defect Software Prediction; Efficient Learning; Robustness; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/8920; https://ink.library.smu.edu.sg/context/sis_research/article/9923/viewcontent/3639478.3641229_pvoa_cc_by.pdf
• Institution: Singapore Management University

Pre-trained language models of code, which are built upon large-scale datasets, millions of trainable parameters, and high computational resources cost, have achieved phenomenal success. Recently, researchers have proposed a compressor-based classifier (Cbc); it trains no parameters but is found to...