# What is the time complexity and space complexity of below code

//Maximum size rectangle binary sub-matrix with all 1s

//Code–>

``````
class Solution {
public static int findMax(int arr[], int n)
{
int res=0,h=0,p=0,i=1;
Stack<Integer> startPos = new Stack<>();
Stack<Integer> height = new Stack<>();
startPos.push(0);
for(i=0;i<n;i++)
{
// Empty or when a bigger value arrives we start a new rectangle
if(height.isEmpty() || arr[i]>height.peek())
{
startPos.push(i);
height.push(arr[i]);
}
// Pop logic
else if( arr[i]<height.peek())
{
while(!height.isEmpty() && arr[i]<height.peek())
{
h=height.pop();
p=startPos.pop();
res=Math.max(res,h*(i-p));
}
// Store the last popped value to retrive the current value's starting
startPos.push(p);
height.push(arr[i]);
}
}
// Remaining values
while(!height.isEmpty())
{
h=height.pop();
p=startPos.pop();
res=Math.max(res,h*(i-p));
}
return res;
}
public int maxArea(int M[][], int n, int m) {
// add code here.
int res=0;
int arr[] = new int[m];

//   Traverse the matrix
for(int i=0;i<n;i++)
{
for(int j=0;j<m;j++)
{
if(M[i][j]==0)
{
arr[j]=0;
}
else
{
arr[j] = arr[j] + M[i][j];
}
}
// Calculate result so far
res=Math.max(res,findMax(arr,m));
}
return res;
}
}
``````

//Testcase example

Input:
n = 4, m = 4
M[][] = {{0 1 1 0},
{1 1 1 1},
{1 1 1 1},
{1 1 0 0}}
Output: 8