In an Array, find the Contiguous Subarray with Sum to a Given Value.

Objective: Given an array and an integer, find the Subarray whose sum is equal to the given integer.

Examples:

```int[] arrA = { 25, 12, 14, 22, 19, 15, 10, 23 };
Integer = 55
Output : 55 is found between indexes 2 and 4
And Elements are : 14 22 19
```

Approach :

Naive Approach: Use 2 loops . Time Complexity – O(n2).

Better Approach: Time Complexity – O(n)

• Idea is to keep adding all the elements to the currSum
• Keep checking if the currSum<Sum
• If currSum gets greater than the Sum then start reducing the currSum from the beginning of the array using “start”if any time currSum=Sum, Stop and return

NOTE: Technique used in this problem can be used to solve the problem “Find a subarray such that the sum of elements in it is equal to zero“. In that the array will aldo have to contain the negative elements and our given sum is zero.

Complete Code:

Output:

```55 is found between indexes 2 and 4
And Elements are :  14 22 19

```

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If you find anything incorrect or you feel that there is any better approach to solve the above problem, please write comment.
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9 Responses

1. Deep Shah says:

I think it can be done in O(n) time using Kadane’s Algorithm (http://en.wikipedia.org/wiki/Maximum_subarray_problem)

• tutorialhorizon says:

Yes it can be, but the solution provided is also O(n).

• Deep Shah says:

This is the other solution which I thought of . It uses only one for loop. and no nested loops inside.

private static int maxSubarray(int[] arr) {

// TODO Auto-generated method stub

int max_sum = 0;

int sum = 0;

int startIndex = 0; // intially start index is at 0

int endIndex = 0; // intially end index is at 0 position

int tempStart = 0; // intially start = tempstart = 0

if(arr.length == 0){

System.out.println(“No Elements in Array”);

return -1;

}

else if(arr.length == 1){

System.out.println(“Array contains only single element”);

startIndex = 0;

endIndex = 0;

System.out.println(“Start Index : “+startIndex + “t End Index :”+endIndex);

return arr[0];

}

for(int i = 0; i<arr.length;i++){

sum = sum + arr[i];

if(max_sum < sum){

max_sum = sum;

startIndex = tempStart; // max_sum < sum so we found a greater sum from last tempstart to current element

endIndex = i; // make end as current element

}

else if(sum < 0){

sum = 0;

tempStart = i + 1; // if sum is less than 0, make a fresh start with right element

}

}

System.out.println("Start Index : "+startIndex + "t End Index :"+endIndex);

System.out.print("Largest Sum is obtained from : ");

for(int i = startIndex; i<= endIndex;i++){

System.out.print(arr[i]+", ");

}

return max_sum;

}

• Holden says:

Have you solved this problem with Kandane’s algorithm? Could you please write your code in Ideone and share its link here?
Since it is not readable here.

2. Holden says:

Thank you for the great post.

Don’t you think this ‘for’:

for (int i = 0; i <= arrA.length; i++) {

should be:

for (int i = 0; i < arrA.length; i++) {

?

3. Holden says:

There is a while in ‘for’ loop, is it still O(n) solution? Your proposed logic seems linear; But in textbooks, we read if there is two nested loop, time complexity will be quadratic.

• Holden says:

I think I got it! These 2 loops are independent! If two loops are not independent, time complexity will be O(n^2). Thank you

• tutorialhorizon says:

Yes holden you got it right. Though there are two nested loops but still every element will be traversed only once.

4. jafar basha says:

In an Array, find the Smallest Contiguous Subarray with Sum to a Given Value.
https://github.com/jafar9/c-prg/blob/master/smallestsubarray.c

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