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Comment by agentultra | Hacker News Reader

Math.

When learning graph theory it can be quite useful at first. But once you start using set theory the graphical representation actually hides more information than it gives and intuition starts to get in the way of us discovering useful properties.

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IMO the graphical representation some times removes accidental complexity by not needing names or producing orderings. eg. To write a non-tree graph you always need to introduce local names unless you use something like SKI combinators. When proving the Kuratowski-Wagner theorem for example, I'm pretty sure the diagrams and the language-form help each other without either being strictly better.

I think this visual stuff is perfect for functional (math based) programming as composed expressions aren't easily readable as english.

I find language to be better suited for imperative procedures. Think about it, I have a list of tasks, do I write that list in ordered English bullet points or do I draw a diagram?

Actually diagram might be better suited, for example to display the difference between sequential in parallel tasks.

I find simple math to be much more elegant and easier to comprehend then a jumbled visual diagram. It's much easier to understand a universal quantification in a standard notation than reasoning by visual analogies.

Programming languages tend to be a little less expressive and elegant. They're more complicated too. For reasons of course... but I don't think I'm going to be writing algorithms and data-structures in such a tedious notation as a diagram.

Graphics are good for some things but programming I don't think is one of them.

Are you familiar with category theory? I've been finding it very helpful for processing things visually. Considering this is "category oriented programming," I'm betting they find it helpful, too ;)

Some things look best in text and it's fine. However, "programming" is a very broad category, and definitely does not boil down only to algorithms and data structures. I'd even say that most programming tasks in the world right now are much less about complex algorithms and much more about everyday systems plumbing. Sure, at some point you'll need to fire a complicated linear algebra kind of algorithm, but before you get there, you need to get the data out from some source, do some reformatting, decide which algorithms to run and when and then send the results somewhere else. And for that, seeing what is happening with your data the moment you try a solution, and deciding the next step based on immediate feedback is great.

This is pretty much why we've gone with interchangeable representations instead of going "visual only". The choice of the proper tools / representations highly depends on the context, and we want to leave that for the programmer's decision.

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