How about this for an idea: a decompiler that uses Machine Learning to name the decompiled variables and functions. Would be nice even if it worked only sometimes.
It basically hashes machine code (with address parts removed) [1], then when reverse engineers label and push symbols to the server (or get them from some debug build), others can pull and see what the functions are called in completely unrelated projects, that use the same libraries / have the same functions.
[0] https://abda.nl/lumen/ [1] https://github.com/naim94a/lumen/issues/2
[0]: https://arxiv.org/abs/1909.09029 / J. Lacomis et al., "DIRE: A Neural Approach to Decompiled Identifier Naming," 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2019, pp. 628-639, doi: 10.1109/ASE.2019.00064.
Wait, did I say it was possible? I'm curious what a neural netted compiler would produce. Probably your average CRUD software.
Better would be a high level description of what’s happening. I have a feeling that would be easier to achieve.