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I have written translators and they are really hard. I think training on code bases is the way to go but I am skeptical overall that it is even worth the effort

I have written translators and they are really hard. I think training on code bases is the way to go but I am skeptical overall that it is even worth the effort. The problem is that the translation doesn't get you all the way there. The code produced is buggy and wrong in most cases. You probably get a better result from re-designing and re-implementing. I wonder what the data being trained on even is. It has to include successful translations, right? There are not many of those. Not enough for a good result.

chiefalchemist 4y ago
I think it depends on how urgent the migration is, and how much you're paying to fix the bugs. If the systems works functionally but the infrastructure (?) hasn't aged well, and there's only time / budget to switch horses, that might be the sweet spot.
jaunkst 4y ago
I’ve written translators that also had to consider pattern changes. The amount of training to translate code effectively is enormous to be effective at scale. I assume this is segmenting separate models based on each language permutation. I would love to see AI applied to predict algorithms and provide intelligent recommendations.