I'm using math in a colloquial sense to refer to "mathy math," not "computer science math." So linear algebra would be a leading example, along with stuff like vectors and complex numbers. Accounting math would be another example, because it requires a bignum implementation that doesn't drop decimals like float can.
I thought his post was pretty clear tbh. For example he mentions complex types so that should be an indicator that he's not talking about the kind of high school maths that the average developer can coast along with.
1) Most of (micro-)benchmarking in computing. Of course you want a tiny bit more analysis in that case.
2) Slightly more real-world: Measuring things when you only have approximate rulers, have difficult things to measure (odd surfaces, etc.), or have to calculate from 2nd hand measurements (pictures with rulers, etc.)
By real world I mean code running in production and making someone money. Or a popular open source package. And I'd be interested in which company or project that is and if they have a writeup.
So for those use cases where you will be using a library with custom types anyway, choose one that doesn't overload the operators for those types? This very much seems like a problem on the library- and not the language-level.
Also, in Rust if you don't want to use the overloading, you can still write your code to directly use function calls `a.add(b)`, where `a` is a type that implements the `Add` trait.
I get the truth in that statement. But as a game programmer, I find it interesting the contrast that linear algebra is precisely what is commonly used.
I mean, most of us aren't going use linear algebra, but still...