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Recursion is equivalent to iteration. You can solve any problem you like with it. The problem with those tutorials is that they’re trying to do two things at o

Recursion is equivalent to iteration. You can solve any problem you like with it. The problem with those tutorials is that they’re trying to do two things at once: 1) teach you Haskell and 2) advocate for Haskell. I’m currently working as a full time assistant for one of the first year computer science courses at my university. This course is taught in a teaching dialect of Racket which does not allow mutation or side effects of any kind. That doesn’t stop the profs from creating assignments with real world applicability such as graffiti stroke recognizers and decision tree learning algorithms. The key is that they’re not trying to make Racket look good, so the patterns of recursion can get pretty ugly at times.

the5avage 6y ago
> Recursion is equivalent to iteration. You can solve any problem you like with it. Maybe my comment was somehow badly written, because you (and the only other reply from chriswarbo) clearly misunderstood me. I know that recursion is equivalent to iteration^^ My point was that some problems fit the one or the other better. Look at fft for example. The algorithm is easy with recursion but hard with iteration. For other problems its the opposite.
- tasuki 6y ago
  Which problems are hard to solve with recursion instead of iteration?
  - the5avage 6y ago
    I found something like splitting a string into words not very intuitive... Also the classical (recursive) fibonacci function everyone shows has accidental complexity of O(2^n). If you want a sane version it looks definitely more complicated than the iterative version. I never saw a recursive version of bresenham's line plotting algorithm so this might be a good candidate as well ;)
    - chongli 6y ago
      I found something like splitting a string into words not very intuitive... Just use a couple of accumulators (one for the current word, one for the list of completed words). Also the classical (recursive) fibonacci function everyone shows has accidental complexity of O(2^n). That's moving the goalposts. If you want a really fast fibonacci function then the classical iterative algorithm [which is O(n)] is not what you want either. Better to use matrix exponentiation which you can implement nicely with recursion using a divide-and-conquer approach similar to mergesort, giving you fibonacci with time O(log(n)). I never saw a recursive version of bresenham's line plotting algorithm so this might be a good candidate as well ;) There's nothing special about Bresenham's line algorithm that would make it particularly challenging to implement with recursion.
    - a1369209993 6y ago
      > splitting a string into words not very intuitive It seems okay? split :: String -> [String] split s = w s "" where w [] "" = [] w [] a = [reverse a] w (' ':ss) "" = w ss "" w (' ':ss) a = reverse a : w ss "" w (c:ss) a = w ss (c:a) If you're done then you're done (and dump the accumulator), if it's a space get rid of it (and dump the accumulator), otherwise add it to the acuumulator. That the accumulator is stored backward is a bit wierd, but seems more a consequence of linked lists than recursion per se.
      - the5avage 6y ago
        Yeah it's ok ;) Going back to my original comment this code is exactly what I meant with "patterns to deal with other problems". You clearly used a pattern (accumulator) with wich you are familiar. Do you agree that most imperative programmers would not come up with this solution on their own, if you didn't teach them the "accumulator pattern"? For me personally a tutorial with a lot code like that would be interesting. Showing me another version of a recursive descent parser doesn't teach me anything, because I know how to write it (with recursion!!!) in an imperative language...
        chongli 6y ago

the5avage 6y ago

> Recursion is equivalent to iteration. You can solve any problem you like with it. Maybe my comment was somehow badly written, because you (and the only other reply from chriswarbo) clearly misunderstood me. I know that recursion is equivalent to iteration^^ My point was that some problems fit the one or the other better. Look at fft for example. The algorithm is easy with recursion but hard with iteration. For other problems its the opposite.

tasuki 6y ago
Which problems are hard to solve with recursion instead of iteration?
- the5avage 6y ago
  I found something like splitting a string into words not very intuitive... Also the classical (recursive) fibonacci function everyone shows has accidental complexity of O(2^n). If you want a sane version it looks definitely more complicated than the iterative version. I never saw a recursive version of bresenham's line plotting algorithm so this might be a good candidate as well ;)
  - chongli 6y ago
    I found something like splitting a string into words not very intuitive... Just use a couple of accumulators (one for the current word, one for the list of completed words). Also the classical (recursive) fibonacci function everyone shows has accidental complexity of O(2^n). That's moving the goalposts. If you want a really fast fibonacci function then the classical iterative algorithm [which is O(n)] is not what you want either. Better to use matrix exponentiation which you can implement nicely with recursion using a divide-and-conquer approach similar to mergesort, giving you fibonacci with time O(log(n)). I never saw a recursive version of bresenham's line plotting algorithm so this might be a good candidate as well ;) There's nothing special about Bresenham's line algorithm that would make it particularly challenging to implement with recursion.
  - a1369209993 6y ago
    > splitting a string into words not very intuitive It seems okay? split :: String -> [String] split s = w s "" where w [] "" = [] w [] a = [reverse a] w (' ':ss) "" = w ss "" w (' ':ss) a = reverse a : w ss "" w (c:ss) a = w ss (c:a) If you're done then you're done (and dump the accumulator), if it's a space get rid of it (and dump the accumulator), otherwise add it to the acuumulator. That the accumulator is stored backward is a bit wierd, but seems more a consequence of linked lists than recursion per se.
    - the5avage 6y ago
      Yeah it's ok ;) Going back to my original comment this code is exactly what I meant with "patterns to deal with other problems". You clearly used a pattern (accumulator) with wich you are familiar. Do you agree that most imperative programmers would not come up with this solution on their own, if you didn't teach them the "accumulator pattern"? For me personally a tutorial with a lot code like that would be interesting. Showing me another version of a recursive descent parser doesn't teach me anything, because I know how to write it (with recursion!!!) in an imperative language...
      - chongli 6y ago