The rapid rise of Large Language Models (LLMs) has changed software development, with tools like Copilot, JetBrains AI Assistant, and others boosting developers' productivity. However, developers now spend more time reviewing code than writing it, highlighting the importance of Code Readability for code comprehension. Our previous research found that existing Code Readability models were inaccurate in representing developers' notions and revealed a low consensus among developers, highlighting a need for further investigations in this field. Building on this, we surveyed 10 Java developers with similar coding experience to evaluate their consensus on Code Readability assessments and related aspects. We found significant agreement among developers on Code Readability evaluations and identified specific code aspects strongly correlated with Code Readability. Overall, our study sheds light on Code Readability within LLM contexts, offering insights into how these models can align with developers' perceptions of Code Readability, enhancing software development in the AI era.

翻译：大型语言模型（LLM）的迅速崛起改变了软件开发，诸如Copilot、JetBrains AI Assistant等工具提升了开发者的生产效率。然而，开发者现在审查代码的时间超过了编写代码的时间，这凸显了代码可读性对于代码理解的重要性。我们先前的研究发现，现有的代码可读性模型在反映开发者认知方面不够准确，并揭示了开发者之间的共识度较低，表明该领域需要进一步研究。在此基础上，我们调查了10位具有相似编码经验的Java开发者，以评估他们在代码可读性评估及相关方面的共识。我们发现开发者在代码可读性评估上存在显著一致性，并识别出与代码可读性高度相关的特定代码特征。总体而言，本研究揭示了LLM背景下的代码可读性问题，为这些模型如何与开发者对代码可读性的认知保持一致提供了见解，从而促进人工智能时代的软件开发。