Explain how to use an AVL tree to sort n comparable elements in O(n log n) time.
insert n elements into an AVL tree. => inserting each element takes O(log(n)) => so, total time complexity of inserting all n elements is O(n log(n)) finding and removing min element from AVL tree takes O(log n) finding and removing min element, n times gives all n elements in sorted order. total time complexity for this operation is O(n log(n)) so, total time complexity is O(n log(n)) + O(n log(n)) = O(n log(n)) this is how we can sort n elements using AVL tree in O(n log(n)) time
Explain how to use an AVL tree to sort n comparable elements in O(n log n) time.
True or false? (a) An insertion in an AVL tree with n nodes requires Θ (log(n)) rotations. (b) A set of numbers are inserted into an empty BST in sorted order and inserted into an empty AVL tree in random order. Listing all elements in sorted order from the BST is O (n), while listing them in sorted order from the AVL tree is O (log(n)). (c) If items are inserted into an empty BST in sorted order, then the...
fill in the blank Binary Search Tree AVL Tree Red-Black Tree complexity O(log N), O(N) in the worst case O(log N) O(log N) Advantages - Increasing and decreasing order traversal is easy - Can be implemented - The complexity remains O(Log N) for a large number of input data. - Insertion and deletion operation is very efficient - The complexity remains O(Log N) for a large number of input data. Disadvantages - The complexity is O(N) in the worst case...
The time-complexity of searching an AVL tree is in the worst case and in the average case. On), On) O(logot). O(log O ON), C(n) 0(), O(log) Question 16 2 pts The time-complexity of searching a binary search tree is in the worst case and in the average case (1), O(log) O(logn), O(log,n) On), On) 001), 001)
Data structures c++ 1- What is the search time in an AVL tree with n nodes. Select one or more: a. O(2^n) b. O(height * log n) c. O(log n) d. O(height) e. O(log height) f. O(n) g. O(1) h. O(2^height)
Assume the following notation/operations on AVL trees. An empty AVL tree is denoted E. A non-empty AVL tree T has three attributes The key T.key is the root node's key. The left child T.left is Ts left subtree, which is an AVL tree (possibly E). The right child T.right is T's right subtree, which is an AVL tree (possibly E). (a) 5 marsl Write a function RANGECOUNT(T, lo, hi) to count the number of nodes in an AVL tree with...
Assume the following notation/operations on AVL trees. An empty AVL tree is denoted E. A non-empty AVL tree T has three attributes: • The key T.key is the root node’s key. • The left child T.left is T’s left subtree, which is an AVL tree (possibly E). • The right child T.right is T’s right subtree, which is an AVL tree (possibly E). (a) [5 marks] Write a function RangeCount(T, lo, hi) to count the number of nodes in an...
When sorting n records, Merge Sort has worst-case running time O(log n) O O(n log n) O O(n) O(n^2)
Q5 Match the following operations to their corresponding worst case time complexities Operations Finding the nert larger item in a Hash Table Time Complexities од) O (log n) O(n) O(n log n) O(n2) o(n3) O(n + m) O(m logn) O((n +m) log n) O(n2+nm) Trying to remove a non-eristing item from a Hash Table 2 3Finding the previous smaller item in a possibly unbalanced BST Updating a previous value into a new value in an AVL Tree Sorting m edges...
1. Consider the following function for an AVL tree with n nodes. void _removeLeftmost(struct Node *cur) { while(cur->left != 0) { cur = cur->left } free(cur); } What is the average case big-O complexity of _removeLeftmost()? a. O(1) b. O(log n) c. O(n) d. None of the above 2. Refer to _removeLeftmost() from Question 1. What is the worst case big-O complexity of _removeLeftmost() for a binary search tree (not necessarily an AVL tree) with n nodes? a. O(1) b. O(log n) c. O(n) d. None of the above
When sorting n records, Merge sort has worst-case running time a. O(n log n) b. O(n) c. O(log n) d. O(n^2)