Forgot about the step between machine code to interpreted, so you are correct it is a 3gl.
However it is still incredibly bold to compare writing sort in C to using Lambda functions Haskell.
How about I throw in some Smalltalk?
Code:
x := SortedCollection new: [:a :b | a > b].
x add: 1; add: 2; add: 3
Note I don't need to tell it to sort/resort.. it does it as I add objects
I'm going to take a guess as I don't know smalltalk that well and say that's a already defined Searching collection written before hand, haskell defines it using a filter function which is essential for list handling.
Am I right about the already defined thing?
Haskell doesn't really have collections like that there just lists, and return new list for every new operation on the list because functional languages are mostly immutable due to the state thing. Pretty much everything in haskell involves some sort of list, and preforming filter map or reduce on it.
The google search engine theory is based on map reduce stuff.
It's the difference between writing an array sort function or calling .sort() in java.
I ain't going to argue against smalltalk though, it pretty much one the languages that implement oo well from what i've learned of it so far. It's got stuff in common with objective C which i know.
Quite, but I don't need to know the somewhat complex algorithms needed to add my delivery to a container, and have it assigned to a van which will be given a delivery address, do I? I just need to know my Delivery object, is contained in a Container object, which in turn is assigned to and contained within a Van object, which has an Address to deliver to.
Although graph theory can find the route for the van, sticking a box in a van object is a trival thing and it is acutally a tree data structure(Graph theory). The van being a node and stuff in it being child nodes.
Finding the route would simply be placing nodes to make a map, and preforming A* on the graph to find the route, the van node would then travel a long the nodes on the graph. Graph theory easily allows you to preform finding roots, whats the most efficent vans for stuff to go in(Might be N-P Complete I'm not sure), and estimated times etc.
The most efficent vans you might have to preform all posible combinations on it, or use a estimated algorithm which is a bit nath really but possibly the only way unless i think about it some more.
If you did not know Graph theory those might be hard problems, yet infact they are trival. Simplifying complexity is what this is about, and it only took me 10 seconds to structure it. It's stuff like this, espically putting stuff in the vans most efficiently to reduce costs, travel, and time to develivery is what saves big companies a lot of money. It may save only 10 pound a van but when you run many vans it's a saving which adds up quickly.
