  Code generation stands as a powerful technique in modern software
development, improving development efficiency, reducing errors, and fostering
standardization and consistency. Recently, ChatGPT has exhibited immense
potential in automatic code generation. However, existing researches on code
generation lack guidance for practical software development process. In this
study, we utilized ChatGPT to develop a web-based code generation platform
consisting of key components: User Interface, Prompt Builder and Backend
Service. Specifically, Prompt Builder dynamically generated comprehensive
prompts to enhance model generation performance. We conducted experiments on 2
datasets, evaluating the generated code through 8 widely used metrics.The
results demonstrate that (1) Our Prompt Builder is effective, resulting in a
65.06% improvement in EM, a 38.45% improvement in BLEU, a 15.70% improvement in
CodeBLEU, and a 50.64% improvement in Pass@1. (2) In real development
scenarios, 98.5% of test cases can be validated through manual validation,
highlighting the genuine assistance provided by the ChatGPT-based code
generation approach.
