Computational Theory Questions
Space complexity refers to the amount of memory or storage space required by an algorithm or program to solve a problem. It measures the maximum amount of memory needed by an algorithm to execute, including both the auxiliary space (extra space required for variables, data structures, etc.) and the input space (space required to store the input data). Space complexity is typically expressed in terms of Big O notation, which provides an upper bound on the growth rate of space usage as the input size increases.