An algorithm's efficiency can be measured by its complexity and its space complexity.

The best case complexity of an algorithm refers to the amount of time or space it can take to execute.

The best case complexity is often used to describe the best possible of an algorithm under certain conditions.

The case complexity of an algorithm refers to the expected amount of time it takes to execute for inputs of typical size.

The complexity of an algorithm describes the total amount of memory space it requires.

The complexity of an algorithm describes the total amount of time it takes to run.

In the context of complexity analysis, the term case refers to the scenario in which the algorithm performs exceptionally well.