Tag: Data Structures and Algorithms Mcq

(A) Maintain sizes (number of nodes) of all trees, and during union
(B) Make smaller tree, the subtree of the larger one
(C) Make the larger tree, the subtree of the smaller one
(D) Implementation: for each root node i, instead of setting parent[i] to -1, set it to -k if tree rooted at i has k nodes

(A) Preorder successor or predecessor
(B) Inorder successor or predecessor
(C) Postorder successor or predecessor
(D) NULL pointers are not replaced

(A) Randomly remove walls until the entrance and exit cells are in the same set
(B) Removing a wall is the same as doing a union operation
(C) Remove a randomly chosen wall if the cells it separates are already in the same set
(D) Do not remove a randomly chosen wall if the cells it separates are already in the same set

(A) It is not a requirement that a find operation returns any specific name, just that finds on two elements return the same answer if and only if they are in the same set
(B) One idea might be to use a tree to represent each set, since each element in a tree has the same root, thus the root can be used to name the set
(C) Initially each set contains one element
(D) Initially each set contains one element and it does not make sense to make a tree of one node only

(A) log (base 2) of n
(B) The number of digits in n (base 10), e.g., 145 has three digits
(C) The square root of n
(D) n

(A) N – (h – 1)
(B) N – (h + 1)
(C) N – 1
(D) N – 1 + h

(A) This dummy node never has a value
(B) This dummy node has always some dummy value
(C) This dummy node has either no value or some dummy value
(D) This dummy node has always some integer value

(A) Binary tree only
(B) Threaded binary tree
(C) Heap data structure
(D) Huffman encoding