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I was surprised to learn that I really enjoy coding, whereas I rather dislike math. I feel like this article might resonate with some people, but not with me.

> Programming languages are implementation tools, not thinking tools. They are strict formal languages invented to instruct machines in a human-friendly way. In contrast, thoughts are best expressed through a medium which is free and flexible.

I don't find math to be "free and flexible," at least, not compared with prose. It's more of an uncomfortable middle ground. When I write code, the computer forces me to be 100% precise and will spit errors at me as soon as I do something wrong. When I write prose, I can sort of proceed however I like within the very broad allowances of English grammar. But when I write math, I feel like I don't know what's allowed and what isn't, what I have to prove and what I can take for granted, what I have to define and what I don't, etc.

> Just as programming languages are limited in their ability to abstract, they also are limited in how they represent data. The very act of implementing an algorithm or data structure is picking just one of the many possible ways to represent it. Typically, this is not a decision you want to make until you understand what is needed.

I disagree pretty strongly on this point. I find that implementing the structures involved in a problem almost always gives me a better understanding of it and helps me find the solution.




> When I write code, the computer forces me to be 100% precise and will spit errors at me as soon as I do something wrong.

This is similar to math though, with the exception that you don't have something or someone telling you that you made a mistake, but you have to seriously question every step in your proof by applying the rules of logic and your knowledge. At a certain point you develop sufficient intuition to spot steps that might be wrong. Most mathematicians ignore steps, which they are not completely confident of being true for the time being, assume the step is true and continue to see whether their derivation leads to what was to be proved, only later checking the steps which they had doubts about. It's more similar to programming than you think. If you like the logical part and algorithmic thinking involved in programming, I'm sure you would also enjoy math if you'd give it a real chance.


Indeed, I'd recommend the "interesting proof" vignettes by 3Blue1Brown: https://www.youtube.com/watch?v=OkmNXy7er84&list=PLZHQObOWTQ...

These are my favorite videos of his


I've found programming is much more like making art or music. You don't have to be "classically trained", and in fact I think the best I've seen aren't.

Not trying to romanticize programming. It is a grueling and frustrating experience in my opinion and experience. But those that are good at it can be exceptional at it.

Development isn't my day job but I read a lot of code and there are those that can write code that is simply beautiful to view and that is highly functional. It truly is an art.

Math is a secondary concern. Sure, if you are working on hardcore algo stuff, it's heavy on math. But the great, great majority of programmers are not doing that. They are writing logic to achieve a business goal using existing primatives.


I think I am reasonably good at math compared to the average person and really loved it growing up and I would also agree that coding is not that similar to it. Coding is a lot more "tactile". It feels much closer to the arts than to math. The idea that we can treat computing as something purely abstract has never come to fruition for me because there are a lot of details in CS and some details matter a lot.

When I was starting out in my career, I worked at a hedge fund. The fund had a bunch of physicists and mathematicians working on models and they actually wrote the code for those models. They wrote some of the worst code I've ever seen. For example, rather than structuring their code properly, they would use exceptions to pass messages around. If function A needed some information from many levels deep in the stack, they would just throw an exception with the message inside. Function A would catch the exception. These aren't actual exceptions but they didn't to refactor their code. As you can imagine their code had horrific performance.

If you abstract away all the details a lot of concepts and constructs in CS look very similar but some of those details that were abstracted away are going to matter a lot when the code is actually run.


> I was surprised to learn that I really enjoy coding, whereas I rather dislike math. I feel like this article might resonate with some people, but not with me.

I posted about this elsewhere in the thread, but a deeper insight for you may be (was for me) that you have an easier time thinking in terms of steps in a process—algorithms—than identities and proofs.


I too like find implementing the structures helps me find the solution. It's quite iterative for me. Also, I think of programming as a mix of math and writing:

https://henrikwarne.com/2019/03/30/programming-math-or-writi...


>I don't find math to be "free and flexible"

Couldn't disagree with that more. That's a language of its own with a lot of extensions and variations introduced by the people involved. Basically any sound formal system (usually the talk's on rings) is viable, therefore math is indeed free and flexible. All you have is to escape the box of spoken language, the same thing as you'd do to learn a programming language if it's not "verbose" enough to make you think in phrases instead of the language in question.


> I don't find math to be "free and flexible," at least, not compared with prose.

Then you haven't done math to a sufficient level. Which most people don't if they aren't math majors.

I'm not talking about calculus or differential equations, etc. Even engineers and CS focuses too entirely on calculation (though CS has its own kind of proofs which are more what I'd call math). Besides mathematicians, only physicists occaisionally look at math this way.

At a certain point, math is about proofs which are a kind of rigorous prose. My math tests in upper level courses were done in essay blue books up to 10 pages of single space text, on one particularly long test.

There are multiple ways to prove a theorem. There are multiple ways to write a program. Some are shorter, some are longer. Some are more cryptic and hard to follow. Some rely on the work of others to outsource your own efforts. They are really quite similar except for math doesn't have a compiler (Coq and it's I'll excluded).




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