  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.
