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.

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