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Comment by im3w1l | Hacker News Reader

How do you cope with the lack of template containers? That's the big thing I miss in C.

Great question! To make things even more annoying - C doesn't have namespaces. So people are forced to write long names like "my_struct_hash_map_t" everywhere, which makes all modern C code look like wall of text (compare too older style code "mshm_t*a = hmalloc()"). To answer honestly - I'm asking myself very pragmatic question: "do I really need a generic code?" much more often compare to C++. In game development C++ templates were used mostly for math libraries (2d/3d/4d vectors, matrices, etc) and containers (hashmap, lists, etc). If we look closely on math libraries we can make a compromise "just float is enough", and if we make such compromise then everything is simple - one don't need templates for math lib anymore, I'm currently using "gb_math.h" [1] and it works pretty good. Containers on the other hand are more challenging, the key here is to understand "can I make this work with linear (maybe static) array?" - and in most cases yes, then you don't need any containers because just arrays will do. If algorithm specific do require a hashmap or list, well, gonna use what we have: macro! It looks weird, and it is weird, but something like khash.h [2] works fine in production.

In reality what it means for me is that I need to spend time making decisions about containers, which is good for game development, as what makes games fun doesn't have any connection to templates. But it also bad for casual non-game related code. I find it much faster to just "hey load this json, do some processing, and save json back" do that in Python than trying to do in C just for sake of C. Ideally namespaces/templates and operator overloading in C would solve all this struggles, but then where C ends and C++ starts?

- [1] https://github.com/gingerBill/gb/blob/master/gb_math.h - [2] https://github.com/attractivechaos/klib/blob/master/khash.h

There's a bizarre lack of interest in CS in the psychology of usable systems - either for developers or for users - which takes into account practical requirements like cycle time.

A lot of CS seems to be story-telling: "This feature makes language X better/worse, because it just does, obviously" with no independent testing or peer review of language productivity and robustness in real work environments.

Well then, so much for it being Computer Science...

As-is, CS really is much closer to a branch of mathematics than a science.

Eh, in a similar way to how theoretical physics is mostly math. Math is the tool you're using, but the assumptions are all based on real-world observations.

I don't know about that; real world observations like what?

Like observations of what can and can't be computed by physical objects. The point of the Church-Turing thesis is that things you prove about Turing machines are proofs about what you can compute in the real world, not just some abstract mathematical model.

Since computers are built by people for people, it does seem like we're missing the most important and difficult science in favor of doing the science that's easy to do. It's easy to reason about how a system that I designed will perform. It's hard to answer the questions of how our technology choices affect other people. It would be great if science could help us design high quality systems with a limited budget, or establish a theory around whether designing any given system will improve someone's life. It would be pretty dang useful if we had some formal scientific results around what makes a game fun, or more generally what makes software pleasant to use and productive.

> establish a theory around whether designing any given system will improve someone's life

That would be sociology or one of its siblings, no?

... or, at best, the piddly "ethics" course that gets tacked on to most undergraduate CS degree programs?

I think that's why Go is so popular right now. I find the language kind of depressing from a PLT perspective, but it was built taking into account practical requirements such as fast compile times, a standard formatting tool, ease of deployment, etc, which makes it a very good system.

Fortunately, computer science still literally means just that - it's an exploration of the properties of computers. As to humans developing computer based systems, yes, scientific rigor is not mandatory, just as you don't require understanding classical mechanics to build an abode. As to the psychology at play with humans developing and using computer based systems, rigorous psychology is eminently suited to your concerns.

I would like you to cite some papers, which claims it makes language X better/worse without any explanation.

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