Consider a binary tree with the following more conditions :Condition ...
The tree is nothing but a balanced BST where the worst case time to find an element = O(logn)
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Consider a binary tree with the following more conditions :Condition ...
Explanation:
Binary Search Tree (BST):
- In a balanced BST, the height of the left subtree and right subtree is approximately the same, with a maximum difference of 1.
- This property helps in reducing the time complexity of search operations.
Worst-case Time Complexity:
- In a balanced BST, the worst-case time complexity to run a membership test for an element is O(logn).
- This is because at each step of the search process, we are able to discard half of the remaining nodes in the tree.
- As a result, the height of the tree plays a crucial role in determining the time complexity of the search operation.
Comparison with Other Options:
- Option 'A' (O(n)) would be the time complexity if the tree was unbalanced, as in the worst case scenario, we would have to traverse through all n nodes.
- Option 'C' (O(n^2)) and Option 'D' (O(nlogn)) are not applicable for a balanced BST, as the time complexity would be much lower due to the balanced nature of the tree.
Therefore, the correct answer is option 'B' (O(logn) ).