The space-complexity of the algorithm is a constant. It just needs space of three integers m, n and t. Thus, the space complexity is O(1).
The time complexity based on the loop and on the condition whether m>n or not. The real issue is how much iteration occurs? The answer based on both m and n.
Best case: If m = n, then there is only one iteration. O(1)
Worst case: If n = 1, then there will m iterations; It is the worst-case (also equivalently, if m = 1 there are n iterations) O(n).
The space complexity of a computer program is the amount of memory needed for its proper execution. The significant concept behind space needed is that unlike time, space can be reused throughout the execution of the program. As discussed, there is frequently a trade-off among the time and space needed to run a program.
In formal definition, the space complexity is described as follows:
Space complexity of Turing Machine: worst case maximum length of the tape needed to process an input string of length n.
The class PSPACE, in complexity theory, is the set of decision problems which can be solved through a Turing machine by using a polynomial amount of memory, and unlimited time.