Given an array arr[] of N integers such that no element is 0 in that array, the task is to find the minimum number of elements to be inserted such that no subarray of the new array has sum 0.
Examples:
Input: N = 3, arr[] = {1, -1, 1}
Output: 2
Explanation: As in the array the sum of first two element is 0 that is 1+(-1) = 0.
To avoid this, insert an element. Insert 10 at position 2.
The array become {1, 10, -1, 1}.
Now the sum of last 2 element is 0. To avoid this insert an element.
Insert 10 at position 4. Array become {1, 10, -1, 10, 1}.
Now, no subarray have sum 0.
So we have to insert minimum 2 integers in the array.Input: N = 4, arr[] = {-2, 1, 2, 3}
Output:
Explanation: No array is there whose sum is 0.
So no need to insert element.
Approach: The problem can be solved based on the following observation.
Observations:
- If we get any subarray with sum 0. Then insert an element just 1 place before the position where you got sum 0. So that sum will not remain 0 and start doing sum again.
- Do the same process till the end and print how many times you have inserted element.
Follow the steps to solve the problem:
- Take an unordered_map to store the sum detail to know if there is a subarray with sum 0.
- Take a variable ans and initialize it to 0 to store the minimum number of elements to be inserted.
- Traverse the array and add every element into the array and also note the sum detail in the map.
- If, you got sum 0 (which can be found by checking if the sum is already present in the map):
- Then increase the ans by 1 and change the sum to the current element value because you have taken care of the previous elements and also remove the entries of the sum from the map.
- Repeat this step whenever there is a subarray with sum 0.
- In last return ans.
Below is the implementation for the above approach.
C++
// C++ code for the above approach: #include <bits/stdc++.h> using namespace std; // Function to find the minimum count // of required insertions int getElements( int N, int arr[]) { // To store the previous sums unordered_map< long long int , int > forSum; // Final answer int ans = 0; // To store current sum long long int sum = 0; // Traversing array for ( int i = 0; i < N; i++) { // Adding elements sum += arr[i]; // Storing occurrence forSum[sum]++; // If found any subarray with sum 0 if (sum == 0 || forSum[sum] > 1) { ans++; // New sum sum = arr[i]; // Clearing previous data forSum.clear(); // Storing new sum forSum[sum]++; } } return ans; } // Driver code int main() { int N = 3; int arr[] = { 1, -1, 1 }; // Function call cout << getElements(N, arr) << endl; return 0; } |
Java
// Java code for the above approach: import java.io.*; import java.util.*; class GFG { // Function to find the minimum count // of required insertions public static int getElements( int N, int arr[]) { // To store the previous sums HashMap<Integer, Integer> forSum = new HashMap<Integer, Integer>(); // Final answer int ans = 0 ; // To store current sum int sum = 0 ; // Traversing array for ( int i = 0 ; i < N; i++) { // Adding elements sum += arr[i]; // Storing occurrence if (forSum.get(sum) != null ) forSum.put(sum, forSum.get(sum) + 1 ); else forSum.put(sum, 1 ); // If found any subarray with sum 0 if (sum == 0 || (forSum.get(sum) != null && forSum.get(sum) > 1 )) { ans++; // New sum sum = arr[i]; // Clearing previous data forSum.clear(); // Storing new sum forSum.put(sum, 1 ); } } return ans; } // Driver Code public static void main(String[] args) { int N = 3 ; int arr[] = { 1 , - 1 , 1 }; // Function call System.out.print(getElements(N, arr)); } } // This code is contributed by Rohit Pradhan |
Python3
# Python code for the above approach # Function to find the minimum count # of required insertions def getElements(N, arr): # To store the previous sums forSum = {} # Final answer ans = 0 ; # To store current sum sum = 0 ; # Traversing array for i in range (N): # Adding elements sum + = arr[i]; # Storing occurrence if ( sum in forSum): forSum[ sum ] + = 1 else : forSum[ sum ] = 1 # If found any subarray with sum 0 if ( sum = = 0 or forSum[ sum ] > 1 ): ans + = 1 # New sum sum = arr[i]; # Clearing previous data forSum.clear(); # Storing new sum if ( sum in forSum): forSum[ sum ] + = 1 else : forSum[ sum ] = 1 return ans; # Driver Code N = 3 ; arr = [ 1 , - 1 , 1 ]; # Function call print (getElements(N, arr)); # This code is contributed by Saurabh Jaiswal |
C#
// C# implementation of above approach using System; using System.Collections.Generic; class GFG { // Function to find the minimum count // of required insertions static int getElements( int N, int [] arr) { // To store the previous sums Dictionary< int , int > forSum = new Dictionary< int , int >(); // Final answer int ans = 0; // To store current sum int sum = 0; // Traversing array for ( int i = 0; i < N; i++) { // Adding elements sum += arr[i]; // Storing occurrence forSum.Add(sum, 1); // If found any subarray with sum 0 if (sum == 0 || forSum[sum] > 1) { ans++; // New sum sum = arr[i]; // Clearing previous data forSum.Clear(); // Storing new sum forSum.Add(sum, 1); } } return ans; } // Driver Code public static void Main() { int N = 3; int [] arr = { 1, -1, 1 }; // Function call Console.Write(getElements(N, arr)); } } // This code is contributed by code_hunt. |
Javascript
<script> // JavaScript code for the above approach // Function to find the minimum count // of required insertions function getElements(N, arr) { // To store the previous sums var forSum = new Map(); //let forSum= new Array(); // Final answer let ans = 0; // To store current sum let sum = 0; // Traversing array for (let i = 0; i < N; i++) { // Adding elements sum += arr[i]; // Storing occurrence forSum[sum]++; // If found any subarray with sum 0 if (sum == 0 || forSum[sum] > 1) { ans++; // New sum sum = arr[i]; // Clearing previous data forSum.clear(); // Storing new sum forSum[sum]++; } } return ans; } // Driver Code let N = 3; let arr = [ 1, -1, 1 ]; // Function call document.write(getElements(N, arr)); // This code is contributed by sanjoy_62. </script> |
2
Time Complexity: O(N) because the array is traversed only once and at most N elements are cleared from the map.
Auxiliary Space: O(N)
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