Auxiliary Code Automatic Generation Algorithm of Intelligent Art Platform Design Framework based on Visual 3D Information Modeling

Auxiliary code automatic generation algorithm of intelligent art platform design framework based on visual 3D information modeling is designed and implemented in the paper. These rule-based methods synthesize natural language sentences directly from the code elements. They are the first successful methods of automatic annotation generation, which lays a foundation for the subsequent research. However, these methods lack portability and flexibility, and can only generate comments for specific code structures In addition, the number of keystrokes in the process of selecting and generating code can reflect the position of the code required by the programmer in the code recommendation list and the accuracy of the code generated by the automatic code generation tool. With these theoretical models, this paper then designs the novel intelligent art platform design framework based on visual 3D information modeling. The model is tested and compared and the performance is shown.