# Order statistic tree using fenwick tree (BIT)

Given an array of integers with limited range (0 to 1000000). We need to implement an Order statistic tree using fenwick tree.
It should support four operations: Insert, Delete, Select and Rank. Here n denotes the size of Fenwick tree and q denotes number of queries.
Each query should be one of the following 4 operations.

• insertElement(x) – Insert element x into Fenwick tree, with O(log n) worst case time complexity
• deleteElement(x) – Delete element x from fenwick tree, with O(log n) worse case time complexity
• findKthSmallest(k) – Find the k-th smallest element stored in the tree, with O(log n * log n) worst case time complexity
• findRank(x) – Find the rank of element x in the tree, i.e. its index in the sorted list of elements of the tree, with O(log n) time complexity

Prerequisite : Binary Indexed Tree or Fenwick Tree

The idea is to create a BIT of size with maximum limit. We insert an element in BIT using it as an index. When we insert an element x, we increment values of all ancestors of x by 1. To delete an element, we decrement values of ancestors by 1. We basically call standard function update() of BIT for both insert and delete. To find rank, we simply call standard function sum() of BIT. To find k-th smallest element, we do binary search in BIT.

 `// C++ program to find rank of an element ` `// and k-th smallest element. ` `#include ` `using` `namespace` `std; ` ` `  `const` `int` `MAX_VAL = 1000001; ` ` `  `/* Updates element at index 'i' of BIT. */` `void` `update(``int` `i, ``int` `add, vector<``int``>& BIT) ` `{ ` `    ``while` `(i > 0 && i < BIT.size()) ` `    ``{ ` `        ``BIT[i] += add; ` `        ``i = i + (i & (-i)); ` `    ``} ` `} ` ` `  `/* Returns cumulative sum of all elements of ` `   ``fenwick tree/BIT from start upto and ` `   ``including element at index 'i'. */` `int` `sum(``int` `i, vector<``int``>& BIT) ` `{ ` `    ``int` `ans = 0; ` `    ``while` `(i > 0) ` `    ``{ ` `        ``ans += BIT[i]; ` `        ``i = i - (i & (-i)); ` `    ``} ` ` `  `    ``return` `ans; ` `} ` ` `  `// Returns lower bound for k in BIT. ` `int` `findKthSmallest(``int` `k, vector<``int``> &BIT) ` `{ ` `    ``// Do binary search in BIT[] for given ` `    ``// value k. ` `    ``int` `l = 0; ` `    ``int` `h = BIT.size(); ` `    ``while` `(l < h) ` `    ``{ ` `        ``int` `mid = (l + h) / 2; ` `        ``if` `(k <= sum(mid, BIT)) ` `            ``h = mid; ` `        ``else` `            ``l = mid+1; ` `    ``} ` ` `  `    ``return` `l; ` `} ` ` `  `// Insert x into BIT. We masically increment ` `// rank of all elements greater than x. ` `void` `insertElement(``int` `x, vector<``int``> &BIT) ` `{ ` `    ``update(x, 1, BIT); ` `} ` ` `  `// Delete x from BIT. We masically decreases ` `// rank of all elements greater than x. ` `void` `deleteElement(``int` `x, vector<``int``> &BIT) ` `{ ` `    ``update(x, -1, BIT); ` `} ` ` `  `// Returns rank of element. We basically ` `// return sum of elements from start to ` `// index x. ` `int` `findRank(``int` `x, vector<``int``> &BIT) ` `{ ` `    ``return` `sum(x, BIT); ` `} ` ` `  `// Driver code ` `int` `main() ` `{ ` `    ``vector<``int``> BIT(MAX_VAL); ` `    ``insertElement(20, BIT); ` `    ``insertElement(50, BIT); ` `    ``insertElement(30, BIT); ` `    ``insertElement(40, BIT); ` ` `  `    ``cout << ``"2nd Smallest element is "` `     ``<< findKthSmallest(2, BIT) << endl; ` ` `  `    ``cout << ``"Rank of 40 is "` `         ``<< findRank(40, BIT) << endl; ` ` `  `    ``deleteElement(40, BIT); ` ` `  `    ``cout << ``"Rank of 50 is "` `         ``<< findRank(50, BIT) << endl; ` ` `  `    ``return` `0; ` `} `

Output:

```2nd Smallest element is 30
Rank of 40 is 3
Rank of 50 is 3
```

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