Pairing Heaps

August 14, 2009

We previously implemented priority queues using leftist heaps. In this exercise we will implement the same library using a different data structure known as a pairing heap. Pairing heaps are an unusual data structure; they are simple to implement, and performance is good, but their time complexity is not proved, only conjectured, and the analysis has defied many good algorithmists. Our presentation is based on Chris Okasaki’s book Purely Functional Data Structures.

Pairing heaps are heap-ordered multi-way trees, with each node of each tree less than its children. A pairing heap is either empty or is a node consisting of an item and a list of pairing heaps, none of which may be empty. The find-first function simply returns the item at the root of the tree of nodes. Merge takes two trees and makes the tree with the larger root the leftmost child of the tree with the smaller root. Insert builds a singleton node, then calls merge.

The fundamental operation on pairing heaps is the delete-first operation, which discards the root of the tree and merges its children in two passes. The first pass runs from left to right, merging child nodes pair-wise, the first child with the second, the third child with the fourth, and so on. The second pass merges the resulting trees, again pair-wise, from right to left.

Your task is to implement priority queues using pairing heaps, using the same interface as the prior exercise. 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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7 Responses to “Pairing Heaps”

  1. […] Remco Niemeijer Righty, I’m back from vacation so let’s get right back to business. In today’s Programming Praxis problem we have another data structure to implement. Let’s get […]

  2. Remco Niemeijer said

    My Haskell solution (see for a version with comments):

    data PairingHeap a = Empty | Node a [PairingHeap a]
    findFirst :: PairingHeap a -> Maybe a
    findFirst Empty      = Nothing
    findFirst (Node n _) = Just n
    merge :: Ord a => PairingHeap a -> PairingHeap a -> PairingHeap a
    merge Empty p = p
    merge p Empty = p
    merge m@(Node x ps) n@(Node y qs) | y < x     = Node y (m:qs)
                                      | otherwise = Node x (n:ps)
    insert :: Ord a => a -> PairingHeap a -> PairingHeap a
    insert x = merge (Node x [])
    deleteFirst :: Ord a => PairingHeap a -> PairingHeap a
    deleteFirst Empty       = Empty
    deleteFirst (Node _ ps) = foldr merge Empty $ pair ps where
        pair (a:b:xs) = merge a b : pair xs
        pair xs       = xs
    fromList :: Ord a => [a] -> PairingHeap a
    fromList = foldr insert Empty  
    toList :: Ord a => PairingHeap a -> [a]  
    toList Empty        = []
    toList n@(Node x _) = x : toList (deleteFirst n)
    pqSort :: Ord a => [a] -> [a]  
    pqSort = toList . fromList
    main :: IO ()  
    main = print $ pqSort [3, 7, 8, 1, 2, 9, 6, 4, 5]  
  3. DS said

    How’s this for a Programming Praxis: Fix your damn website so it does not break in Opera when you get 1/3 of the way down the front page.

  4. Vikas Tandi said

    my implementation in C

    #include <stdlib.h>
    typedef struct PairingHeapNode
    	int							key;
    	struct	PairingHeapNode*	child;
    	struct	PairingHeapNode*	sibling;
    	struct	PairingHeapNode*	prev;
    static PairHeap* merge_subheaps(PairHeap *p, PairHeap *q);
    static PairHeap* combine_siblings(PairHeap *p);
    PairHeap* PairHeap_insert(PairHeap *p, int key)
    	PairHeap *node;
    	node = (PairHeap*)malloc(sizeof(*node));
    	if(node == NULL)
    		return NULL;
    	node->key = key;
    	node->child = node->sibling = node->prev = NULL;
    	if(p == NULL)
    		return node;
    		return merge_subheaps(p, node);
    PairHeap* PairHeap_DecreaseKey(PairHeap *p, PairHeap *pos, int d)
    	if(d < 0)
    		return p;
    	pos->key = pos->key - d;
    	if(p == pos)
    		return p;
    	if(pos->sibling != NULL)
    		pos->sibling->prev = pos->prev;
    	if(pos->prev->child = pos)
    		pos->prev->child = pos->sibling;
    		pos->prev->sibling = p->sibling;
    	p->sibling = NULL;
    	return merge_subheaps(p, pos);
    PairHeap* PairHeap_DeleteMin(int *key, PairHeap *p)
    	PairHeap *new_root;
    	if(p == NULL)
    		return NULL;
    		*key = p->key;
    		if(p->child != NULL)
    			new_root = combine_siblings(p->child);
    	return new_root;
    static PairHeap* combine_siblings(PairHeap *p)
    	PairHeap *tree_array[1024];
    	int i, count;
    	if(p->sibling == NULL)
    		return p;
    	for(count = 0; p != NULL; count++)
    		tree_array[count] = p;
    		p->prev->sibling = NULL;
    		p = p->sibling;
    	tree_array[count] = NULL;
    	for(i = 1; i < count; i++)
    		tree_array[i] = merge_subheaps(tree_array[i-1], tree_array[i]);
    	return tree_array[count-1];
    static PairHeap* merge_subheaps(PairHeap *p, PairHeap *q)
    	if(q == NULL)
    		return p;
    	else if(p->key <= q->key)
    		q->prev = p;
    		p->sibling = q->sibling;
    		if(p->sibling != NULL)
    			p->sibling->prev = p;
    		q->sibling = p->child;
    		if(q->sibling != NULL)
    			q->sibling->prev = q;
    		p->child = q;
    		return p;
    		q->prev = p->prev;
    		p->prev = q;
    		p->sibling = q->child;
    		if(p->sibling != NULL)
    			p->sibling->prev = p;
    		q->child = p;
    		return q;
  5. […] a program to implement the algorithm described above, using the Scheme programming language. First, here is a library implementation of priority queues using the pairing heap […]

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