With the development of artificial intelligence, machine learning has been applied in more and more domains. In order to improve the quality and efficiency of software, automatic program generation is becoming a research hotspot. In recent years, machine learning has also been gradually applied in automatic program generation. Decision trees, language models, and cyclic neural networks have been applied in code generation, code completion and code knowledge mining. The efficiency of software development has been improved to a certain extent using machine learning. Aimed at the automatic program generation, this paper analyzes and summarizes the models of machine learning, the modifications involved in the models and the application effects. The research direction is discussed from the aspects of programmer behavior and automatic program generation of machine learning.