[xpaulbettsx]

> This is what makes Stack Overflow so helpful, the accompanying natural language description of intentionality or special cases, even if the code that is found isn’t precisely what’s needed, it demonstrates directionally what to do.

You're entirely right, but if you're in an incredibly huge monorepo like Facebook, this information literally doesn't exist; that's part of the problem that Aroma is trying to solve - "how can we show people the Facebook App Way To Do That Thing, even if That Thing doesn't have current documentation"

(Disclaimer: I worked on the coding environment UX for Aroma)

[mlthoughts2018]

Wouldn’t it make more sense to spend the effort annotating these things? Or building models to provide the annotation? I mean, I work professionally in embedding models for computer vision and NLP, and my reaction to the article is that this seems like totally the wrong approach. You’re putting all this effort to create the embedding model out of the part that is both most superficial and least human interpretable (the AST).

[franklsf]

Building models for natural language _and_ code for either NL/intent-based code search or automatically annotating code is indeed another hot research area!

I'd argue Aroma solves a different problem in that it surfaces more idiomatic patterns based on the code you already have. This also can be important especially in production environment, when you need to do things "the right way".