Rivera, Leanne DONE

[leannerivera]

Time complexity: O9n) linear, as it is dependent on how many rows and columns must be converted from 1s to 0s

Space complexity: O(n) linear, as it is dependent on the number of zeros in each row and column of the matrix

[shrutivanw]

Nice work!

While explaining time and space complexities in terms of n, always explain what n is in the input. If n is the number of rows multiplied by number of columns in the input matrix, then your explanation is correct. I would however encourage you to explain the time complexity in terms of the number of rows and the number of columns.

So, if there are n rows and m columns in the input matrix, then your current algorithm will have the space complexity of O(n*m). You could optimize the space complexity further by maintaining two separate arrays: one array which is n row to track which rows should be converted to 0 and another which is m long to track which columns should be converted to zero. Here's my attempt at such an approach: https://github.com/Ada-C10/matrix_convert_to_zero/blob/solution-basic/lib/matrix_convert_to_zero.rb