To the extent that there will be further research on this problem, I think it will be driven by machine learning. We're already seeing this with autocompletion with TabNine, and no reason a similar approach couldn't work for the other issues facing draft code.
If you had a large dataset of keystroke-by-keystroke edit streams, you'd be able to match up erroneous code with the eventual fix. Google or Facebook could absolutely capture these datasets for their internal work if they wanted, and I suspect the results could be scary-good. They wouldn't be able to release the models, though, even for their open source work (Chromium and Android), because it would have such a high chance of revealing internal secrets.