Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers

arXiv:2401.06461v3 Announce Type: replace-cross
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