Is my algorithm gobbling space?: Understanding space complexity

In post about time complexity last fortnight, we saw how we can choose the fastest among multiple algorithms by evaluating their time complexities. Sometimes speed may not be our concern, but rather conserving space inside a tiny device. So we may opt for an algorithm that takes up less space while executing. The space taken up by an algorithm is also called its footprint. Let’s understand how to use space complexity to determine how much footprint an algorithm will take.

How long will my algorithm take?: Understanding time complexity

A software application is a combination of algorithms working together to do tasks for you. But how can we determine which algorithm to use for a specific problem? One way to choose is by evaluating the time that an algorithm will take to solve a problem and how much memory it will consume. To objectively measure the two quantities, we have two methods called time complexity and space complexity respectively. In this post, we will look at time complexity to determine if our algorithm is fast or slow.