The space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely.

Similar to time complexity, space complexity is often expressed asymptotically in big O notation, such as ${\displaystyle O(n),}$ ${\displaystyle O(n\log n),}$ ${\displaystyle O(n^{\alpha }),}$ ${\displaystyle O(2^{n}),}$ etc., where n is a characteristic of the input influencing space complexity.