问题描述
是否曾经尝试过在反编译中利用人工神经网络?如果有可能在神经网络中提供源代码的简化语义以及代码，以便它可以学习两者之间的联系，那就太好了.我认为如果进行了优化，这可能会失去有效性，也许对于高级语言也可能会更好，但是我很想听听任何人对此进行的尝试.
Has there ever been any attempts at utilizing artificial neural networks in decompilation? It would be nice if it was possible to provide the trimmed semantics of source along with the code in to a neural network so it could learn the connection between the two. I assume this would likely lose it's effectiveness when there is optimizations and maybe work better for high level languages too but I'm interested in hearing any attempts anyone has had at this.
推荐答案
我假设您的意思是与Assembly相比，将其反编译为人类可读的C/C ++，
I'm assuming you mean decompilation to human readable C/C++ as compared to Assembly then,
鉴于简洁代码的输入大小(优化/编译后的代码)和输出大小，以及反分解过程的多行有状态性质，我想尽管这是ANN可以处理的更大问题.
Given the input size (optimized/compiled code) and the output size of succinct code, and the multi-line stateful nature of decomplilation process, I would have though this is a larger problem that a ANN could ever handle.
这篇关于ANN反编译器?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！