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By changing the NULL lines in a binary tree to the special links called threads, it is possible to execute traversal, insertion and deletion without using either a stack or recursion.
In a right in threaded binary tree each NULL link is replaced by a particular link to the successor of that node under the inorder traversal called right threaded. Using right threads we shall find it easy to perform an inorder traversal of the tree, since we need to only follow either an ordinary link or a threaded to find the next node to visit.
If we replace each NULL left link by a particular link to the predecessor of the node known as left threaded under inorder traversal the tree is called as left in threaded binary tree. If both the left and right threads are present in tree then it is called as fully threaded binary tree for example:
The maximum degree of any vertex in a simple graph with n vertices is (n-1) is the maximum degree of the vertex in a simple graph.
Tree is dynamic data structures. Trees can expand & contract as the program executes and are implemented via pointers. A tree deallocates memory whereas an element is deleted.
Channel access In first generation systems, every cell supports a number of channels. At any given time a channel is allocated to only one user. Second generation systems also
For AVL trees the deletion algorithm is a little more complicated as there are various extra steps involved in the deletion of node. If the node is not a leaf node, then it contain
Following are some of the drawback of sequential file organisation: Updates are not simply accommodated. By definition, random access is impossible. All records should be
Adjacency list representation An Adjacency list representation of Graph G = {V, E} contains an array of adjacency lists mentioned by adj of V list. For each of the vertex u?V,
Q. Write down an algorithm to insert a node in the beginning of the linked list. Ans: /* structure containing a link part and link part
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A depth-first traversal of a tree visits a nodefirst and then recursively visits the subtrees of that node. Similarly, depth-first traversal of a graph visits a vertex and then rec
Example 3: Travelling Salesman problem Given: n associated cities and distances among them Find: tour of minimum length that visits all of city. Solutions: How several
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