The question is about the time complexity of deleting an item in a binary heap.
A binary heap is a complete binary tree, which can be efficiently implemented as an array. The operations on a binary heap, like insert, delete, and extract max (or min for a min heap), involve maintaining the heap property after the operation. This is usually done using a procedure called "heapify" or "sift-down" that moves a node down the tree, swapping it with its children until the heap property is restored.
The operation delete(i) is supposed to delete the i-th node in the heap. Deleting a node involves two steps:
- Replace the node to be deleted with the last node in the heap.
- Heapify the heap to restore the heap property.
The replacement operation takes constant time, O(1), because we're dealing with an array and we have direct access to any element.
Heapify is the operation that can take more time. In the worst case, a node might have to be moved down the tree all the way to the leaf level. Since the heap is a complete binary tree, its depth d is approximately equal to log(n) where n is the number of nodes in the heap.
Therefore, the worst-case time complexity of the delete(i) operation is dominated by the heapify step, which is O(d), where d is the depth of the heap.
So, the answer to the question is "2. $O(d)$ but not $O(1)$"