I didn't mean to use denoising process directly to reverse engineering. I was just thinking the idea of `step-by-step reverting` could be used in some ML model for reverse engineering.

Though you have a point. Unlike denoising process, reverse engieering would require change of dimensions in the middle steps, making it more difficult than denoising.

Just crawling open source codes and compiling the code with the special compiler would produce a massive amount of training data. If the special compiler I mentioned in the post is easy to make.

I didn't mean to use the model used in stable diffusion process for reverse engineering.

I was just thking this step-by step reverting training process could be used in some model for reverse engineering.