A data structure is required for storing a set of integers such that each of the following operations can be done in (log n) time, where n is the number of elements in the set.
o Deletion of the smallest element o Insertion of an element if it is not already present in the set
Which of the following data structures can be used for this purpose?
(A)
A heap can be used but not a balanced binary search tree
(B)
A balanced binary search tree can be used but not a heap
(C)
Both balanced binary search tree and heap can be used
(D)
Neither balanced binary search tree nor heap can be used
Answer: (B)
Explanation:
A self-balancing balancing binary search tree containing n items allows the lookup, insertion, and removal of an item in O(log n) worst-case time. Since it\’s a BST, we can easily find out minimum element in O(nlogn). See our post Find the minimum element in a Binary Search Tree for details. Since Heap is a balanced binary tree (or almost complete binary tree), insertion complexity for heap is O(logn). Also complexity to get minimum in a min heap is O(logn) because removal of root node causes a call to heapify (after removing the first element from the array) to maintain the heap tree property. But a heap cannot be used for the above purpose as the question says – insert an element if it is not already present. For a heap, we cannot find out in O(logn) if an element is present or not. Thanks to game for providing the correct solution.
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