Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.
  • ☆ Yσɠƚԋσʂ ☆@lemmy.mlOP
    6·
    2 months ago

    I’ve found coding assistance to be pretty lacklustre myself as well. That said, one area where language models might actually be good is emulating a type system for dynamic languages. Given how good these things are at figuring out general shape of the code, I suspect they could fairly accurately tell you argument and return types for functions. And you could probably get away with a pretty small model if it only targets a specific language.

    • Kache@lemm.ee
      61·
      2 months ago

      Dedicated incremental static type checkers for dynamic languages already exist. In particular, Pyright for Python is fantastic and in many ways surpasses the type systems of classic typed languages

      • ☆ Yσɠƚԋσʂ ☆@lemmy.mlOP
        1·
        2 months ago

        I’m not too familiar with tooling for Python, but my experience is that you get fairly limited support in dynamic languages unless you start adding hints. Ultimately, a static type checker can’t resolve information that’s not there.

  • 1984@lemmy.today
    72·
    2 months ago

    For devops, it’s amazing. We use many tools that we are not experts in, and it’s incredible to get ready to use code examples how to configure them for various scenarios.

    I save many hours every week using open Ai latest models.

    • mihor@lemmy.ml
      11·
      2 months ago

      I used it for GUI code as well, I hate frontend work so that saves me quite some time getting all the forms together with a few prompts.