Exploring Distributional Shifts in Large Language Models for Code Analysis
Shushan Arakelyan,
Rocktim Das,
Yi Mao
et al.
Abstract:We systematically study how three large language models with code capabilities -CodeT5, Codex, and ChatGPT -generalize to out-ofdomain data. We consider two fundamental applications -code summarization, and code generation. We split data into domains following its natural boundaries -by an organization, by a project, and by a module within the software project. We establish that samples from each new domain present all the models with a significant challenge of distribution shift. We study how established meth… Show more
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