Looking for examples of AI slop code and pull requests for research purposes

Depending on how willing I'm with recording myself, I will either record a video essay, or at least write some article about the subject. I will also do some research into permissive and "more rational" AI policies of open source projects and them becoming sponsored by AI vendors (there's a very sad trend there).

31 points · 7 comments · view on lemmy.world

7 Comments

harcesz@szmer.info · 13 pts · 20d

Searching for github repos with ai brand name author or co-authors should provide plenty examples. Single commit claimed as version 1.0 from a few months earlier with no changes since is another guaranteed way to identify one. I wish all slopcoders a very get a life already.

one_old_coder@piefed.social · 12 pts · 20d
  • Find some specific markdown files on Github like agent.md or agents.md or claude.md. You'll get a big list in no time.
  • Also filter the repos who have huge readme.md with a lot of emojis.
  • Last but not least, find the commits that contain Co-authored-by: GitHub Copilot <copilot@github.com> or stuff like that.
fargeol@lemmy.world · 8 pts · 20d (2 replies)

You can have a look at Claude's contributions on Github, but if you want whole vibe-coded projects, here's Bun, which was (poorly) rewritten in Rust from Zig or Ferrite a vibe-coded Markdown editor.
Both projets use Rust for various reasons, do you have a preference for a language or another?

ZILtoid1991@lemmy.world · 3 pts · 20d (1 reply)

While Rust is not my main language, I can understand it enough to compare it to well formatted Rust code, as well as will use Rust to showcase why natural language programming is bad and confusing even though we're taking keywords from natural languages (and let is a great example of that, especially how Rust uses it). I already seen Bun, and forgot about it🤪.

wewbull@feddit.uk · 5 pts · 19d

The problem with slop code is not superficial.

The game the machine is playing is " reproduce text that looks like all the other text you've seen before". As such the code will look good, read well, etc. The problem is that the problems are hidden. Incongruent logic between parts of the same program. Subtle "unintentional" behaviour. Bug fixes which force an outcome rather than remove a fundamental issue.

Apart from excessive verbosity it can be hard to see the issues.

Luccus@feddit.org · 5 pts · 20d

A lot of local LLM front-ends are obviously vibe coded by LLM enthusiasts using their local models. You can also check for Claude.md or AGENTS.md in a repo.

northernlights@lemmy.today · 1 pts · 19d

Here's a PR that I thought was just a massive waste of time: https://github.com/rhinstaller/anaconda/pull/7074