Skew Heap

03 Feb, 2021
A skew heap (or self – adjusting heap) is a heap data structure implemented as a binary tree. Skew heaps are advantageous because of their ability to merge more quickly than binary heaps. In contrast with binary heaps, there are no structural constraints, so there is no guarantee that the height of the tree is logarithmic. Only two conditions must be satisfied : 
The general heap order must be there (root is minimum and same is recursively true for subtrees), but balanced property (all levels must be full except the last) is not required.Main operation in Skew Heaps is Merge. We can implement other operations like insert, extractMin(), etc using Merge only.
The general heap order must be there (root is minimum and same is recursively true for subtrees), but balanced property (all levels must be full except the last) is not required.
Main operation in Skew Heaps is Merge. We can implement other operations like insert, extractMin(), etc using Merge only.
Example : 1. Consider the skew heap 1 to be  
2. The second heap to be considered 
4. And we obtain the final merged tree as  
Recursive Merge Process : merge(h1, h2) 
Let h1 and h2 be the two min skew heaps to be merged. Let h1’s root be smaller than h2’s root (If not smaller, we can swap to get the same).We swap h1->left and h1->right.h1->left = merge(h2, h1->left)
Let h1 and h2 be the two min skew heaps to be merged. Let h1’s root be smaller than h2’s root (If not smaller, we can swap to get the same).
We swap h1->left and h1->right.
h1->left = merge(h2, h1->left)
Examples : 
Let h1 be
        10
     /    \
   20      30
  /        /
40        50

Let h2 be
       15
     /    \
   25      35
  /  \
45    55

After swapping h1->left and h1->right, we get
        10
     /    \
   30      20
  /        /
50        40

Now we recursively Merge
   30
   /     AND   
  50

       15
     /    \
   25      35
  /  \
45    55
After recursive merge, we get (Please do it 
using pen and paper).
        15
     /     \
   30        25
  /  \     /    \
35    50  45    55

We make this merged tree as left of original
h1 and we get following result.
             10
         /         \
       15           20
    /      \       /   
   30       25    40   
 /   \    /    \
35   40  45    55
For visualization : https://www.cs.usfca.edu/~galles/JavascriptVisual/LeftistHeap.html 
CPP
// CPP program to implement Skew Heap// operations.#include <bits/stdc++.h>using namespace std; struct SkewHeap{    int key;    SkewHeap* right;    SkewHeap* left;     // constructor to make a new    // node of heap    SkewHeap()    {        key = 0;        right = NULL;        left = NULL;    }     // the special merge function that's    // used in most of the other operations    // also    SkewHeap* merge(SkewHeap* h1, SkewHeap* h2)    {        // If one of the heaps is empty        if (h1 == NULL)            return h2;        if (h2 == NULL)            return h1;         // Make sure that h1 has smaller        // key.        if (h1->key > h2->key)           swap(h1, h2);         // Swap h1->left and h1->right        swap(h1->left, h1->right);         // Merge h2 and h1->left and make        // merged tree as left of h1.        h1->left = merge(h2, h1->left);         return h1;    }     // function to construct heap using    // values in the array    SkewHeap* construct(SkewHeap* root,                     int heap[], int n)    {        SkewHeap* temp;        for (int i = 0; i < n; i++) {            temp = new SkewHeap;            temp->key = heap[i];            root = merge(root, temp);        }        return root;    }     // function to print the Skew Heap,    // as it is in form of a tree so we use    // tree traversal algorithms    void inorder(SkewHeap* root)    {        if (root == NULL)            return;        else {            inorder(root->left);            cout << root->key << "  ";            inorder(root->right);        }        return;    }}; // Driver Codeint main(){    // Construct two heaps    SkewHeap heap, *temp1 = NULL,                   *temp2 = NULL;    /*            5           / \          /   \         10   12    */    int heap1[] = { 12, 5, 10 };    /*            3           / \          /   \         7     8        /       /      14    */    int heap2[] = { 3, 7, 8, 14 };    int n1 = sizeof(heap1) / sizeof(heap1[0]);    int n2 = sizeof(heap2) / sizeof(heap2[0]);    temp1 = heap.construct(temp1, heap1, n1);    temp2 = heap.construct(temp2, heap2, n2);     // Merge two heaps    temp1 = heap.merge(temp1, temp2);    /*            3           / \          /   \         5     7        / \   /       8  10 14      /     12    */    cout << "Merged Heap is: " << endl;    heap.inorder(temp1);}
The heap obtained after merging is: 
12  8  5  10  3  14  7
 
Akanksha_Rai
immanuelidun10
Advanced Data Structure
Heap
Heap
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