# Space complexity

## Computer memory needed by an algorithm / From Wikipedia, the free encyclopedia

#### Dear Wikiwand AI, let's keep it short by simply answering these key questions:

Can you list the top facts and stats about Space complexity?

Summarize this article for a 10 years old

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.[1] This includes the memory space used by its inputs, called **input space**, and any other (auxiliary) memory it uses during execution, which is called **auxiliary space**.

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