Set Matrix Zeroes

To solve this coding challenge, we need to update an \( m \times n \) matrix such that if an element is 0, its entire row and column are set to 0. The constraint is that it should be done in place without using extra space beyond O(1), which means modifying the matrix directly without using additional arrays or lists of size proportional to \( m \) or \( n \).

Explanation

Approach:
  1. Identify Rows and Columns with Zeroes:
    • Iterate over the matrix to identify which rows and columns need to be set to zero.
    • Instead of using extra storage, we can use the first row and the first column of the matrix itself to store this information.
    • Use two flags,
      row_zero
      and
      col_zero
      , to keep track of whether the first row or first column should be zeroed out.
  2. Mark the Zeroes:
    • During the iteration, if a cell contains zero, set the corresponding first row and first column cells to zero.
    • Also, if the zero is in the first row or first column, set the respective flag to true.
  3. Update the Matrix:
    • Iterate through the matrix again (excluding the first row and column), and for each cell, if its corresponding first row or first column cell is zero, set the cell to zero.
  4. Zero Out the First Row and Column:
    • Finally, check the
      row_zero
      and
      col_zero
      flags and zero out the first row and first column if needed.
Detailed Steps in Pseudocode:
Step 1: Initialize Variables and Flags
                                            
# initialize dimensions of the matrix
rows = length(matrix)
cols = length(matrix[0])

# flags to check if first row or first column should be zeroed
row_zero = False
col_zero = False

                                        
Step 2: Identify Rows and Columns to be Zeroed
                                            
for i from 0 to rows - 1:
    for j from 0 to cols - 1:
        if matrix[i][j] == 0:
            # mark the first cell of current row and column
            matrix[0][j] = 0
            matrix[i][0] = 0
            
            # mark if the zero is in the first row or column
            if i == 0:
                row_zero = True
            if j == 0:
                col_zero = True

                                        
Step 3: Update the Matrix Based on Markers
                                            
for i from 1 to rows - 1:
    for j from 1 to cols - 1:
        if matrix[i][0] == 0 or matrix[0][j] == 0:
            matrix[i][j] = 0

                                        
Step 4: Zero Out the First Row and Column if Needed
                                            
if row_zero:
    for j from 0 to cols - 1:
        matrix[0][j] = 0

if col_zero:
    for i from 0 to rows - 1:
        matrix[i][0] = 0

                                        
Summary:
By using the first row and the first column of the matrix to store markers, we avoid the need for additional storage space. This approach ensures the solution is efficient in terms of both time and space complexity. Specifically, the algorithm operates in O(m * n) time complexity and O(1) extra space complexity, which adheres to the constraints provided.