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by philsnow
940 days ago
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I don't know if [0] would be any help, it doesn't talk about graphs in particular but does talk about functional-focused approaches to data structures. This note[1] on the wikipedia page for the book says it better than I could: > [...] consider a function that accepts a mutable list, removes the first element from the list, and returns that element. In a purely functional setting, removing an element from the list produces a new and shorter list, but does not update the original one. In order to be useful, therefore, a purely functional version of this function is likely to have to return the new list along with the removed element. In the most general case, a program converted in this way must return the "state" or "store" of the program as an additional result from every function call. Such a program is said to be written in store-passing style. [0] https://www.cs.cmu.edu/~rwh/students/okasaki.pdf [1] https://en.wikipedia.org/wiki/Purely_functional_data_structu... |
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The issue is that it is hard to do on complex graph structures in an algorithm where incremental changes happen to the graph O(n) times - it ends up creating complex code and complex execution that might be slow to pass the time limit on Codeforces, let's say.
In the OCaml world maybe this is the place where you say "screw it, this abstracted function does some stateful temporary business, but it looks pure from the outside" but in Haskell it's a lot harder to pull off without going deep into monads (and I forget how those work every time).