This whole thread seems to be unaware about Debian… so I’ll give an actual answer.

Debian only actually updates their software packages every 2 years, this is for stability purposes. However you still need to fix some severe bugs so about every 2-3 months Debian does point releases that are only updating for security fixes. This is one of them.

When Debian 14 actually releases it will upgrade nearly all of the packages that are in your base system.

Chatgpt just cribs from stack overflow, which in turn just cribs their answers from documentation. Once you figure that out, they both become surprisingly useless.

The bizarre thing is that they are only analysing something like 40 programs/library. You could reach the same conclusion clicking through their gitlab for a few minutes.

The translation rate is the actually interesting part.

“Game dev… Just force Rust into it”

What’s wrong with Rust for game dev? It seems similar to C++, and C# which are the dominant languages.

I can see arguments that the current projects have poor approaches, but not that the language itself is ill-suited.

Debían developer is a specific position that you apply for. Anyone can be a maintainer. Well, I had to get approved but I don’t know the qualifications, I already had code in Debían vía GNOME.

“just how many people are fucking terrible at their jobs”.

Apparently so. When I review mathematics software it’s clear that non-mathematicians have no clue what they are doing. Many of them are subtlely broken, they use either trivial algorithms or extremely inefficient implementations of sophisticated algorithms (e.g trial division tends to be the most efficient factorization algorithm because they can’t implement anything else efficiently or correctly).

The only difference I’ve noticed with the rise of LLM coding is that more exotic functions tend to be implemented, completely ignoring it’s applicability. e.g using the Riemann Zeta function to prove primality of an integer, even though this is both very inefficient and floating-point accuracy renders it useless for nearly all 64-bit integers.

bc can handle extended-precision integers, unlike bash which maps them to floats.

These might be of interest to software developers but it’s all just style nothing here actually effects the computation. The problem I encounter with LLMs is that they are incapable of doing anything but rehearsing the same algorithms you get off of blogs. I can’t even successfully force them to implement a novel algorithm they will simply deny that it is valid and revert back to citing their training data.

I don’t see LLMs actually furthering the field in any real way ( even if by accident, since they can’t actually perform deductive reasoning).

I think that there are certain attitudes that mainly occur to people outside the domain. Like how people endlessly shit on open-source projects, but few of those people are ever actually at the wheel of one.

Not hentai but “Anubis”, the webscraper deterrent has an anime girl and it looks quite unprofessional, and what’s worse is something like balancing Anubis’ scales would be a much better image than a girl with a magnifying glass.

If what the original commenter said is true about simply replacing keywords with another string, then it’s questionable if they are actually learning anything about language design or demonstrating skill.

“Take them at their word”

Who? Has there been a survey of contributors?

“Genuinely think that coreutils would be better if it were written in Rust”

I feel like the skill-level of the contributors is high enough that they would not be so naive.

Programs in different languages can compile to the same machine code. Any advantage would be in language constructs. But if you already have an existing C implementation what advantage do you do from a Rust implementation?

I personally write in 3 languages: Rust, C++, and Fortran ( or rarely SPARK). I don’t port my code across languages, because there is no advantage. If I wanted it better, I would work on my existing codebase.

Porting really only helps if the original language was hindering development, deployment or runtime. These arguments don’t really hold with C, a fast, low-dependency language that is more widely used than Rust.

Being written in Rust has mixed effects. Rust is still less mainstream than C, so fewer people can contribute. However, it does attract more interest because it’s different.

However, the reasons why you create/contribute to new-but-similar projects is to add functionality that the original project doesn’t have. By nature a coreutils replacement has to behave like coreutils or else it will break many configurations. This severely limits the functionality you can provide. So why are people (and Canonical) contributing so much labor to something that still doesn’t function as intended?

I say it’s the licensing. I say this as someone who regularly gets requests to change the licensing of my software (more than any feature request). I think licensing is a big deal, and most software devs recognize that.

You are fixating on the incorrect premise. I noted that it was started a decade ago as a analogy for how labor intensive the project is. A project that by design has to mirror the behaviour of coreutils.So why are people investing the time in this? What makes it worthwhile? It’s the permissive license. If uutils used GPL individuals would instead try to contribute to the much more utilised coreutils, where their contributions would be guaranteed to have an impact.

Edit: Some of the earlier issues date from 2013, so it has been a decade, although it probably was very obscure at the time.

I’m fairly certain that people who advocate for teaching ethics, only do it under the assumption that people are being taught to do what the proponent wants. In reality learning ethics is just learning different theories of ethics.

But the permissive license is why it gained traction, otherwise who would spend so much resources on something that a decade later only accomplishes 85 percent of what coreutils does?

The only code generation assistance I use is in the form of compilers. For fun I tried to use the free version of Chatgpt to replicate an algorithm I recently designed and after about half-hr I could only get it to produce the same trivial algorithms you find on blog posts even with feeding it much more sophisticated approaches.