A research team at Peking University recently launched an innovative tool called ChatCoder, aiming to solve the difficulties of programmers in expressing code requirements. This tool gradually refines and defines code requirements in two stages by simulating conversations with users, thereby significantly improving the execution accuracy of large models in code generation tasks.
In the design of ChatCoder, the research team emphasized the importance of manual intervention. Through interaction with users, ChatCoder can more accurately capture and understand user needs, and then generate code that meets expectations. This method not only improves the efficiency of code generation, but also reduces the error rate of large models in practical applications.
The paper points out that manual intervention plays a key role in the process of demand refinement. Through continuous conversations with users, ChatCoder can gradually clarify the details of the requirements, avoiding the ambiguity or misunderstanding that big models may appear during code generation. This interactive requirement refinement method provides more accurate guidance for code generation of large models.
Through this innovative method, the big model can better meet users' code needs, promoting further development in the field of code generation. The launch of ChatCoder not only provides programmers with an efficient tool, but also opens up new possibilities for the application of large models in code generation tasks.
In general, ChatCoder's research and development marks an important breakthrough in the field of code generation for big models. By combining manual intervention and intelligent dialogue, this tool provides an effective solution to the problem of expressing programmers' needs, and is expected to promote the further development and application of code generation technology in the future.