this post was submitted on 29 Aug 2023
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Programming
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I think code golf is a great dataset for this kind of analysis specifically because they are artificial and people are paying attention to the number of characters used. Leetcode solutions might be a better option though.
In real world projects there are too many confounding factors. People aren’t implementing servers in brainfuck or websites in C. Even rewrites of a project into another language have more/fewer features. So it’s an apples to oranges comparison.
But a big problem with this dataset is error handling - or really the complete lack thereof. Real code needs to deal with errors and they can add a lot depending on the language.
I was very surprised to see rust and go so close as I find go vastly more verbose due to error handling and need to reimplement things like searching a list. But code golf type problems ignore these types of things that you see in real code.
So there is not really and useful conclusion that can be made except if you spend all day writing code golf problems.
That’s true, and you can also combine multiple errors to have a single catch block or handle each error separately. The perfect dataset for this comparison will need to be written. Code golf data is good enough for a non-academic fun analysis like this one.