In recent years, the programming capabilities of Artificial Intelligence (AI) have been continuously evolving, but they have not yet reached perfection. Recently, Max Woolf, a senior data scientist at BuzzFeed, discovered through experiments that if continuous prompts for 'writing better code' are provided to large language models (LLMs), AI can indeed generate higher quality code. This finding has garnered widespread attention, with renowned AI scientists emphasizing the importance of iteration and prompt design. In Woolf's experiment,

OpenAI researchers announced the launch of CriticGPT on Thursday, an innovative AI model designed to identify and correct errors in code generated by ChatGPT. This breakthrough marks a significant advancement in AI technology's ability to self-improve and ensure quality control.

42% of survey participants have already used AI in the software development process. 57% of professional respondents believe AI improves code quality. 46% of respondents reported an increase in job satisfaction. 44% of survey participants noted that AI has saved costs.

AI models still exhibit numerous API misuse issues when addressing Java coding questions. The API misuse rates for GPT-3.5 and GPT-4 are 49.83% and 62.09%, respectively. There is a significant gap between the enhancement of large language models' code generation capabilities and the reliability and robustness of the generated code.