> There is an enormous amount of computer science that most programmers are completely unfamiliar with, especially within academic CS: programming-language theory, type theory, formal semantics, compiler theory, algorithmic research, complexity theory, distributed computing theory, verification, cryptography, computational geometry, numerical methods, and so on. Being proficient in one narrow area does not automatically give you the prerequisites for another.

And the difficult part of all those areas of computing is the mathematics part. Which I think is what I am arguing, mathematics is a fundamentally different type of "difficult" to any other subject.

PLT and such isn't math conceptually sure it's all logical maths of some kind but largely it's not maths in the traditinal sense of how we understand maths.

Because otherwise if you think about it all of computing is Maths but with computers...

I don't think people who read the Wireless Fidelity spec can understand any of it in a weekend or anything even to a rough extent.

Similarly with websockets, quic etc. the most you can take away without much prior knowledge is what it does which maps into Maths as well.

Every quantifiable science has some amount of math, but it's by definition applied math. I think this was more of a debate between applied and more abstract math.