What is space complexity in algorithms?

What is space complexity in algorithms?

Space complexity measures the amount of working storage an algorithm needs. It includes both the space for inputs and the space for auxiliary variables.

Can you give me an example of calculating space complexity?

Sure! For a simple algorithm that uses an array of size n, the space complexity is O(n) because it requires space proportional to the input size.

What are the different types of space complexity?

There are two main types: fixed space complexity, which is constant regardless of input size, and variable space complexity, which changes with input size.

How does space complexity affect algorithm performance?

Higher space complexity can lead to increased memory usage, which may slow down performance, especially in memory-constrained environments.

What is the difference between time complexity and space complexity?

Time complexity measures the time an algorithm takes to complete, while space complexity measures the memory it uses.