Queues

November 1, 2013

One of the basic data structures in computer science is the queue, in which items are inserted into the data structure and retrieved in the order in which they were inserted; the standard operations on a queue are enqueue, dequeue, and isEmpty.

Your task is to write functions to implement a queue. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

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Posted by programmingpraxis
Filed in Exercises
5 Comments »

5 Responses to “Queues”

  2. Adolfo Pérez Álvarez (@xardon) said
    November 3, 2013 at 12:42 AM

    Implementation in SML.

    signature QUEUE = sig
    type 'a queue

    exception EmptyQ

    val empty: 'a queue
    val enqueue: 'a queue -> 'a -> 'a queue
    val dequeue: 'a queue -> 'a * 'a queue
    val isEmpty: 'a queue -> bool
end

structure ListQueue :> QUEUE = struct
    type 'a queue = 'a list * 'a list

    exception EmptyQ

    val empty = ([], [])

    fun enqueue (xs, ys) x = (x::xs, ys)

    fun dequeue ([], [])    = raise EmptyQ
      | dequeue (xs, [])    = dequeue ([], rev f)
      | dequeue (xs, y::ys) = (y, (xs, ys))

    fun isEmpty ([], []) = true
      | isEmpty _        = false
end
  3. Matt Harrison (@mt_harrison) said
    November 3, 2013 at 2:43 PM 

    var Queue = function (items) {
    this.elements = items || [];
};

Queue.prototype.enqueue = function (item) {
    this.elements.push(item);
    return this;
};

Queue.prototype.dequeue = function () {
    return this.elements.shift();
};

Queue.prototype.isEmpty = function () {
    return this.elements.length === 0;
};

window.tasksQueue = new Queue(["Wake Up", "Shower"]);

tasksQueue.enqueue("Dress")
    .enqueue("Have Breakfast")
    .enqueue("Go to work");

while(!tasksQueue.isEmpty()) {
    console.log(tasksQueue.dequeue());
}
  4. treeowl said
    December 26, 2013 at 7:56 PM

    Okasaki “banker’s queues” in Haskell:

    import Prelude hiding (head,tail)
import qualified Prelude as P

data Queue a = Q [a] {-# UNPACK #-} !Int [a] {-#UNPACK#-} !Int

-- toList is faster than just removing items one at a time because it avoids all the queue rotations.
toList :: Queue a -> [a]
toList (Q fs _ rs _) = fs ++ reverse rs

-- fromList is faster than just snocing items on one at a time because it
-- avoids all the queue rotations. It also produces a queue in the optimal state, with everything in the front list.
fromList :: [a] -> Queue a
fromList l = Q l (length l) [] 0

size (Q _ flen _ rlen) = flen+rlen

emptyq = Q [] 0 [] 0

head :: Queue a -> a
head (Q [] _ _ _) = error "Cannot get the head of an empty queue."
head (Q (h:_) _ _ _) = h

tail :: Queue a -> Queue a
tail (Q [] _ _ _) = error "Cannot get the tail of an empty queue."
tail (Q (f:fs) flen rs rlen) = queue fs (flen-1) rs rlen

snoc :: Queue a -> a -> Queue a
snoc (Q fs flen rs rlen) x = queue fs flen (x:rs) (rlen+1)

queue :: [a] -> Int -> [a] -> Int -> Queue a
queue f flen r rlen
  | flen >= rlen = Q f flen r rlen
  | otherwise = Q (f++reverse r) (flen+rlen) [] 0
  5. treeowl said
    December 26, 2013 at 7:58 PM

    I forgot to mention above that if the size operation is not needed, it’s possible to save a bit of space by storing only the difference between the front and rear lengths, rather than the lengths themselves.

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