Maybe it's enlightening to see a functional take on that as well.
If you think a bit about this, producing all members of a powerset basically comes down to go over all elements of the input-set.
For every such you have the choice of including it in a subset or not (so you can directly see that there will be 2n subsets for a set of size n)
This idea directly translates into this (yeah sorry it's Haskell):
if you've got the empty set (really a list here but hey FP right?) the only subset of this is the empty-subset itself
or else you have a set with at least one element x (and possible more elements xs)
now you have two classes ob subsets: one where x is included, and one where it is not
you get both by recursively getting all the subsets of the remaining elements xs - just include x everywhere in one copy (that's the map (x:) part - ++ just concatenates the two sets ob subsets
call me weird but I consider that easier to read and reason about than the imperative Java solution ;)
This is what I like about declarative and functional code :)
It's pure :)
I have to add that I have a place also for imperative code, what I do like about imperative code is that instead of repeating the definition (which is not a bad thing it's beautiful), I'm actually taking the mini steps and it makes me understand what's happening better. (that's at least how I understand things).
In addition, let's say I to log something out to the logger, I'm not sure what would happen to the functional code, or I would need to send some metrics to monitoring, I'm sure there is a functional solution to it (monad and friends) but this is where things get's heavy on me.
depends on what you want to log I guess (seems doubtful, that you want to log anything here - indeed I never had the need to log anything inside a pure function as you can test it anytime if you know the input to it)
but sure most of us learned programming in the more operational/imperative mindset (basically by doing step-by-step debugging in our head) so it might take some time to get "warm" with FP ;)
But in those more mathematical problems (where the problem often is recursive in nature) it's just a natural fit ;)
I remember this firmly as one of the more difficult exercises in my introductory programming course at university. But finding that solution was so rewarding!
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Maybe it's enlightening to see a functional take on that as well.
If you think a bit about this, producing all members of a powerset basically comes down to go over all elements of the input-set.
For every such you have the choice of including it in a subset or not (so you can directly see that there will be 2n subsets for a set of size n)
This idea directly translates into this (yeah sorry it's Haskell):
meaning:
if you've got the empty set (really a list here but hey FP right?) the only subset of this is the empty-subset itself
or else you have a set with at least one element
x
(and possible more elementsxs
)x
is included, and one where it is notxs
- just includex
everywhere in one copy (that's themap (x:)
part -++
just concatenates the two sets ob subsetscall me weird but I consider that easier to read and reason about than the imperative Java solution ;)
This is definitely beautiful! :)
This is what I like about declarative and functional code :)
It's pure :)
I have to add that I have a place also for imperative code, what I do like about imperative code is that instead of repeating the definition (which is not a bad thing it's beautiful), I'm actually taking the mini steps and it makes me understand what's happening better. (that's at least how I understand things).
In addition, let's say I to log something out to the logger, I'm not sure what would happen to the functional code, or I would need to send some metrics to monitoring, I'm sure there is a functional solution to it (monad and friends) but this is where things get's heavy on me.
depends on what you want to log I guess (seems doubtful, that you want to log anything here - indeed I never had the need to log anything inside a pure function as you can test it anytime if you know the input to it)
but sure most of us learned programming in the more operational/imperative mindset (basically by doing step-by-step debugging in our head) so it might take some time to get "warm" with FP ;)
But in those more mathematical problems (where the problem often is recursive in nature) it's just a natural fit ;)
cool, adding the scala functional :: recursive :: declarative :: concise way to the post :)) .
I remember this firmly as one of the more difficult exercises in my introductory programming course at university. But finding that solution was so rewarding!