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Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers
March 26, 2024, 4:52 a.m. | Yuling Shi, Hongyu Zhang, Chengcheng Wan, Xiaodong Gu
cs.CL updates on arXiv.org arxiv.org
Abstract: Large language models have catalyzed an unprecedented wave in code generation. While achieving significant advances, they blur the distinctions between machine- and human-authored source code, causing integrity and authenticity issues of software artifacts. Previous methods such as DetectGPT have proven effective in discerning machine-generated texts, but they do not identify and harness the unique patterns of machine-generated code. Thus, its applicability falters when applied to code. In this paper, we carefully study the specific patterns …
abstract advances arxiv authenticity code code generation cs.ai cs.cl cs.se human integrity language language models large language large language models machine patterns programmers software type
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