## Google Interview Question

**Country:**United States

Kadane algorithm gives sum of the largest continuous subarray , task is to find elements of that largest subarray as @zr.roman bro already commented above

actually, Kadane is a correct approach, but the algorithm should be modified to keep track of the starting and ending indices of the maximum subarray.

@ zr.roman yup, Kadane is correct approach in modified way, thats how i solved the problem but didnot mention algo name in my code, so i want to know is it necessary to tell name of the algo to interviewer, as i am preparing for my tech interviews or implementation is enough??

actually, I don't know. Well, by default, the more you tell the better.

As I understand the interviewer when he gives such a task, he wants to know the approach.

For example, this task can be solved with 3 approaches:

1) brute force O(n^2),

2) divide'n'conquer O(n log n)

3) DP O(n).

I think, that is the basis.

Moreover, in CLRS textbook the DP approach is described but not mentioned that it is Kadane.

```
public static ArrayList findConsecutiveMaxSum(int[] nums){
if(nums.length<1) return null;
ArrayList<Integer> res = new ArrayList<>();
int maxSofar, currMax,startIndx =0,endIndx =0;
maxSofar = currMax = nums[0];
for (int i = 1 ; i< nums.length ;i++){
if(currMax + nums[i] < nums[i]) startIndx = i;
currMax = Math.max(nums[i],currMax+nums[i]);
if(maxSofar<currMax) endIndx = i;
maxSofar = Math.max(maxSofar,currMax);
}
for (int i = startIndx ; i<=endIndx ;i++) res.add(nums[i]);
if(endIndx<startIndx) res.add(nums[endIndx]);
return res;
}
```

The below code will give you max Sum in O(N).

We just have to get the startIndex and endIndex(when you make tempSum 0) and get the values in-between them.

```
public static int maxSum(int[] numbers)
{
/*
* Handle Edge cases
* 1. is input Array is NULL
* 2. If input Array has only one element
*/
if(numbers == null)
{
return -1;
}
int maxSum = 0;
int tempSum = 0;
// int numbers[] = { 1 , 3 , -5 , 3 , 2 , 1 , -3 , 4 , 2 , -12 , 2 , 3}
// Iterating through the array 0...N
for(int i=0; i< numbers.length; i++)
{
// Adding it to temp Sum
tempSum = tempSum + numbers[i];
if(maxSum < tempSum)
{
maxSum = tempSum;
}
// If temp Sum is less than 0, making it to Zero.
// Ex: 1 + 3 + -5 = -1. In this case, making tempSum to Zero, so that -1 doesnt affect the sum of the next sequence
else if(tempSum < 0)
{
tempSum = 0;
}
}
return maxSum;
}
```

modified Kadane.

c#

```
private static int[] Kadane( int[] arr ) {
var coords = new int[2] { 0, 0 };
int maxByNow = arr[ 0 ], greatest = arr[ 0 ];
for (int i = 1; i < arr.Length; i++) {
if ( maxByNow < 0 ) { coords[ 0 ] = i; }
maxByNow = Math.Max( arr[ i ], maxByNow + arr[ i ] );
var tmp = Math.Max( greatest, maxByNow );
if ( tmp > greatest ) { coords[ 1 ] = i; }
greatest = tmp;
}
int[] res = new int[ coords[ 1 ] > coords[ 0 ] ? coords[ 1 ] - coords[ 0 ] + 1 : 1 ];
res[ 0 ] = arr[ coords[ 1 ] ];
for ( int i = coords[ 0 ]; i <= coords[ 1 ]; i++ ) {
res[ i - coords[ 0 ] ] = arr[ i ];
}
return res;
}
```

O(N) solution in Python

returns a list of consecutive numbers with the biggest sum

```
def findConsecutiveIntegerBiggestSum(l):
if type(l) != list:
raise Exception('input is not a list')
if len(l) == 0:
raise Exception('list is empty')
accum_li = [0] * len(l)
accum = 0
ct_pos = 0
for i, v in enumerate(l):
accum += v
accum_li[i] = accum
if v > 0:
ct_pos += 1
if ct_pos < 2:
return [max(l)]
best_sum = accum_li[-1]
best_low = 0
best_high = len(l) - 1
curr_low = 0
curr_high = len(l) - 1
while(curr_high - curr_low > 1):
curr_sum = accum_li[curr_high] - accum_li[curr_low]
if curr_sum > best_sum:
best_sum = curr_sum
best_low = curr_low + 1
best_high = curr_high
if l[curr_low] > l[curr_high]:
curr_high -= 1
else:
curr_low += 1
return l[best_low : best_high + 1]
```

- Python

- O(N)

- needs two pass over entire list

- returns a list containing consecutive numbers which give the max sum

```
def findConsecutiveMaxSum(l):
if type(l) != list:
raise Exception('input is not a list')
if len(l) == 0:
raise Exception('list is empty')
accum_li = [0] * len(l)
accum = 0
ct_pos = 0
#first pass: integrate over list
for i, v in enumerate(l):
accum += v
accum_li[i] = accum
if v > 0:
ct_pos += 1
if ct_pos < 2:
return [max(l)]
best_sum = accum_li[-1]
best_low = 0
best_high = len(l) - 1
curr_low = 0
curr_high = len(l) - 1
#second pass: try to improve sum
while(curr_high - curr_low > 1):
curr_sum = accum_li[curr_high] - accum_li[curr_low]
if curr_sum > best_sum:
best_sum = curr_sum
best_low = curr_low + 1
best_high = curr_high
if l[curr_low] > l[curr_high]:
curr_high -= 1
else:
curr_low += 1
return l[best_low : best_high + 1]
```

I'm preparing to apply for tech companies next months and wanted to ask you guys. How on earth am I supposed to know there is an algorithm called "Kadane algorithm" would solve this problem? Do you learn that at school? (I'm from a different country)

My thinking of tech interviews was that it measures how someone could find a solution for a given problem in a short period of time, not memorize unknown algorithms and write them down at the time of interview. So frustrating.

This code returns a list of the elements that gives the max sum, the code uses dynamic programming

```
public List<int> FindMaxSum(int[] values)
{
int sum = values[0];
int index = 0;
int maxSum = values[0];
int maxIndex = 0;
int minIndex = 0;
for (int i = 1; i < values.Length; i++)
{
if (sum + values[i] > values[i])
{
sum += values[i];
}
else
{
sum = values[i];
index = i;
}
if (sum > maxSum)
{
maxSum = sum;
maxIndex = i;
minIndex = index;
}
}
var result = new List<int>();
for (int i = minIndex; i <= maxIndex; i++)
result.Add(values[i]);
return result;
}
```

Prints the largest sum, and the start/end indices (indices begin from 0). Change array vars and length if needed.

```
#include <stdio.h>
main()
{
int nums[100] = {-2,1,-3,4,-1,2,1,-5,4}, length = 9, i = 0, j = 0;
int largestSum = 0, largestSumBegin = 0, largestSumEnd = 0;
int tempSum = 0, tempSumBegin = 0;
for (i = 0; i < length; i++) {
if (i == 0) {
largestSum = tempSum = nums[i];
}
tempSum += nums[i];
if (tempSum > largestSum) {
largestSum = tempSum;
largestSumBegin = tempSumBegin;
largestSumEnd = i;
}
if (tempSum < 0) {
tempSum = 0;
tempSumBegin = i+1;
}
}
printf("\nlargest sum = %d, start idx = %d, end idx = %d", largestSum, largestSumBegin, largestSumEnd);
```

}

```
#include <stdio.h>
main()
{
int nums[100] = {-2,1,-3,4,-1,2,1,-5,4}, length = 9, i = 0, j = 0;
int largestSum = 0, largestSumBegin = 0, largestSumEnd = 0;
int tempSum = 0, tempSumBegin = 0, tempSumEnd = 0;
for (i = 0; i < length; i++) {
if (i == 0) {
largestSum = tempSum = nums[i];
}
tempSum += nums[i];
if (tempSum > largestSum) {
largestSum = tempSum;
largestSumBegin = tempSumBegin;
largestSumEnd = i;
}
if (tempSum < 0) {
tempSum = 0;
tempSumBegin = i+1;
}
}
printf("\nlargest sum = %d, start idx = %d, end idx = %d", largestSum, largestSumBegin, largestSumEnd);
```

}

```
void max_sum_cons(const int* arr, const int n)
{
int starting_pt[n];
int sums[n];
sums[0] = arr[0];
starting_pt[0] = 0;
int max_sum = sums[0];
int max_loc = 0;
for(int i = 1; i < n; ++i)
{
if(sums[i-1] > 0)
{
sums[i] = sums[i-1] + arr[i];
starting_pt[i] = starting_pt[i-1];
if(max_sum <= sums[i])
{
max_sum = sums[i];
max_loc = i;
}
}
else
{
sums[i] = arr[i];
starting_pt[i] = i;
if(max_sum <= sums[i])
{
max_sum = sums[i];
max_loc = i;
}
}
}
for(int i = starting_pt[max_loc]; i <= max_loc; ++i)
std::cout << arr[i] << " ";
std::cout << std::endl;
}
```

```
void max_sum_cons(const int* arr, const int n)
{
int starting_pt[n];
int sums[n];
sums[0] = arr[0];
starting_pt[0] = 0;
int max_sum = sums[0];
int max_loc = 0;
for(int i = 1; i < n; ++i)
{
if(sums[i-1] > 0)
{
sums[i] = sums[i-1] + arr[i];
starting_pt[i] = starting_pt[i-1];
if(max_sum <= sums[i])
{
max_sum = sums[i];
max_loc = i;
}
}
else
{
sums[i] = arr[i];
starting_pt[i] = i;
if(max_sum <= sums[i])
{
max_sum = sums[i];
max_loc = i;
}
}
}
for(int i = starting_pt[max_loc]; i <= max_loc; ++i)
std::cout << arr[i] << " ";
std::cout << std::endl;
}
```

My version in Python, O(n):

```
from sys import maxint
def max_subarray(A):
max_ending_here = max_so_far = 0
index_low = index_high = 0
negative_case = -maxint
for x in A:
if max_ending_here + x > 0:
max_ending_here += x
else:
max_ending_here = 0
index_low = A.index(x) + 1
if max_ending_here > max_so_far:
max_so_far = max_ending_here
index_high = A.index(x)
if x > negative_case:
negative_case = x
if sum(A[index_low:index_high]) == 0:
return negative_case
return max_so_far,index_low,index_high,A[index_low:index_high + 1]
A = [-2,-7,-6,-4,-1,-5,-8,-1,-7]
print max_subarray(A)
```

My version in Python, O(n)

```
from sys import maxint
def max_subarray(A):
max_ending_here = max_so_far = 0
index_low = index_high = 0
negative_case = -maxint
for x in A:
if max_ending_here + x > 0:
max_ending_here += x
else:
max_ending_here = 0
index_low = A.index(x) + 1
if max_ending_here > max_so_far:
max_so_far = max_ending_here
index_high = A.index(x)
if x > negative_case:
negative_case = x
if sum(A[index_low:index_high]) == 0:
return negative_case
return max_so_far,index_low,index_high,A[index_low:index_high + 1]
A = [-2,-7,-6,-4,-1,-5,-8,-1,-7]
print max_subarray(A)
```

int main()

{

int arr[5]={-2,5,-1,7,-3};

int i,j,k,counter,sum,l,m,temp;

temp=0;

int n;

for(i=0;i<5;i++)

{

counter=-1;

for(j=0;j<=i;j++)

{

counter++;

k=counter;

sum=0;

for(l=0;l<5-i;l++)

{

sum=sum+arr[k];

k=k+1;

}

printf("%d",sum);

if(sum>temp)

{

temp=sum;

}

}

}

printf(" biggest sum from give array:=>%d",temp);

return 0;

}

```
long ConsecutiveLargestSum(vector<long>& data, vector<long>& result)
{
long max_ending_here = 0, max_so_far = 0;
vector<long>::iterator start, end;
for (vector<long>::iterator it = data.begin(); it != data.end(); it++) {
max_ending_here += *it;
if (max_ending_here < 0) {
max_ending_here = 0;
start = end = data.begin();
}
if (max_so_far < max_ending_here) {
max_so_far = max_ending_here;
if (start == data.begin())
start = it;
end = it;
}
}
result.assign(start, end + 1);
return max_so_far;
}
```

Recursive Approach:

```
from sys import maxint
def max_subarray(A):
if not A:
return -maxint
max_sub = A[0]
sum_subarray = 0
for i in range(len(A)):
sum_subarray += A[i]
if sum_subarray < 0:
break
if max_sub < sum_subarray:
max_sub = sum_subarray
return max(max_sub,max_subarray(A[i+1:]))
A = [-3,20,50,300,-400,80,10,-4]
print max_subarray(A)
A = [-3,-5,-4]
print max_subarray(A)
A = [-3,20,50,-400,80,10,-4]
print max_subarray(A)
A = [-3,20,50,-40,80,10,-4]
print max_subarray(A)
A = [-30,20,50,-400,80,10,10,-400,100,20,-40]
print max_subarray(A)
```

```
public static void main(String args[]){
int[] arr = {-2,5,3,-1,7,-3};
int arrLen = arr.length;
int maxSum = 0;
String str ="";
String maxStr = "";
for (int i = 2; i <= arrLen; i++){
for (int j=0; j< arr.length; j++){
int temp =0;
int k = j;
str ="";
while (k < j+i && (j+i <arrLen)){
temp += arr[k];
str = str + " " + arr[k];
k++;
}
if (temp > maxSum){
maxSum = temp;
maxStr = str;
}
}
}
System.out.println("Sum : " + maxSum);
System.out.println(maxStr);
}
```

Kadane algorithm in Java

- t@_@n February 09, 2016