All in all - I hope you keep up the good work, solid tutorials like these make it more compelling to keep up with the basics and learn new things from the "CS 101" department.
Do you plan to add more algorithms?
But, I might try again, or find a different approach to represent some slightly more complicated algorithms. Quicksort and some type of Btree would likely be next on my list, if I feel I can do them justice.
And, yes, including some kind of self-balancing tree would seem to be a good idea. But how the heck does one discuss such things concisely and simply? I couldn't say.
In any case, nice site.
data Heap k v = Empty | Heap k v [Heap k v]
merge Empty h = h
merge (Heap k1 v hs) h@(Heap k2 _ _) | k1 <= k2 = Heap k1 v (h:hs)
merge a b = merge b a
extractmin (Heap k v hs) = (v, foldr merge Empty hs)
insert h k v = merge h (Heap k v [])
Honestly, though, I don't think such a thing is what this website is aiming at. It seems to be more for the established, widely used stuff.
Still nice, though. (It's cute how, for so many of the "heap" data structures, the merge operation is really all you need to give much thought to. See also Binomial Heap, etc.)
> These 6 lines of code provide a heap data structure with amortized logarithmic time for extractmin and constant time insertion and merging (!).
Hmmm ... maybe. We need to be exceptionally careful in our reasoning about time complexity, when the code uses lazy evaluation (perhaps more careful than people know how to be, yet).
A tip: It would be better if you could expand on the "Real World" section, especially when it comes to specific examples (e.g. dictionaries etc). That way, more students would relate to understanding exactly how those data structures are used in practical applications.