Has anyone tried to rewrite some popular open source project with IA? I imagine modern LLMs can be very effective at license-washing/plagiarizing dependencies, it could be an interesting new benchmark too

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gorkaerana 7 hours ago | parent | next [-]

I think it's fair enough to consider porting a subset of rewriting, in which case there are several successful experiments out there:

- JustHTML [1], which in practice [2] is a port of html5ever [3] to Python.

- justjshtml, which is a port of JustHTML to JavaScript :D [4].

- MiniJinja [5] was recently ported to Go [6].

All three projects have one thing in common: comprehensive test suites which were used to guardrail and guide AI.

References:

1. https://github.com/EmilStenstrom/justhtml

2. https://friendlybit.com/python/writing-justhtml-with-coding-...

3. https://github.com/servo/html5ever

4. https://simonwillison.net/2025/Dec/15/porting-justhtml/

5. https://github.com/mitsuhiko/minijinja

6. https://lucumr.pocoo.org/2026/1/14/minijinja-go-port/

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EmilStenstrom 5 hours ago | parent | next [-]

As the author, it's a stretch to say that JustHTML is a port of html5ever. While you're right that this was part of the initial prompt, the code is very different, which is typically not what counts as "port". Your mileage may wary.

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daxfohl 7 hours ago | parent | prev | next [-]

Interesting, IIUC the transformer architecture / attention mechanism were initially designed for use in the language translation domain. Maybe after peeling back a few layers, that's still all they're really doing.

	▲	nathan_compton 6 hours ago \| parent [-]
		This has long been how I have explained LLMs to non-technical people: text transformation engines. To some extent, many common, tedious, activities basically constitute a transformation of text into one well known form from another (even some kinds of reasoning are this) and so LLMs are very useful. But they just transform text between well known forms.

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MrJohz 3 hours ago | parent | prev [-]

Note that it's not clear that any of the JustHTML ports were actually ports per se, as in the end they all ended up with very different implementations. Instead, it might just be that an LLM generated roughly the same library several different times.

See https://felix.dognebula.com/art/html-parsers-in-portland.htm...

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benhoyt 8 hours ago | parent | prev | next [-]

Not me personally, but a GitHub user wrote a replacement for Go's regexp library that was "up to 3-3000x+ faster than stdlib": https://github.com/coregx/coregex ... at first I was impressed, so started testing it and reporting bugs, but as soon as I ran my own benchmarks, it all fell apart (https://github.com/coregx/coregex/issues/29). After some mostly-bot updates, that issue was closed. But someone else opened a very similar one recently (https://github.com/coregx/coregex/issues/79) -- same deal, "actually, it's slower than the stdlib in my tests". Basically AI slop with poor tests, poor benchmarks, and way oversold. How he's positioning these projects is the problematic bit, I reckon, not the use of AI.

Same user did a similar thing by creating an AWK interpreter written in Go using LLMs: https://github.com/kolkov/uawk -- as the creator of (I think?) the only AWK interpreter written in Go (https://github.com/benhoyt/goawk), I was curious. It turns out that if there's only one item in the training data (GoAWK), AI likes to copy and paste freely from the original. But again, it's poorly tested and poorly benchmarked.

I just don't see how one can get quality like this, without being realistic about code review, testing, and benchmarking.

	▲	CuriouslyC an hour ago \| parent [-]
		To be fair, good benchmarking is hard, most people get it wrong. Scientific training helps.

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4 hours ago | parent | prev | next [-]

[deleted]

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hedgehog 3 hours ago | parent | prev [-]

I used one of the assistants to reverse and rewrite a browser-hosted JS game-like app to desktop Rust. It required a lot of steering but it was pretty useful.