Editing Algorithmic efficiency (section)

{{Distinguish|text=[[program optimization]], [[optimizing compiler]], [[loop optimization]], [[object code optimizer]]}}
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In [[computer science]], '''algorithmic efficiency''' is a property of an [[algorithm]] which relates to the amount of [[computational resource]]s used by the algorithm. Algorithmic efficiency can be thought of as analogous to engineering [[productivity]] for a repeating or continuous process.

For maximum efficiency it is desirable to minimize resource usage. However, different resources such as [[Time complexity|time]] and [[Space complexity|space]] complexity cannot be compared directly, so which of two algorithms is considered to be more efficient often depends on which measure of efficiency is considered most important.

For example, [[bubble sort]] and [[timsort]] are both [[Sorting algorithm|algorithms to sort a list]] of items from smallest to largest. Bubble sort organizes the list in time proportional to the number of elements squared (<math display="inline">O(n^2)</math>, see [[Big O notation]]), but only requires a small amount of extra [[computer memory|memory]] which is constant with respect to the length of the list (<math display="inline">O(1)</math>). Timsort sorts the list in time [[linearithmic]] (proportional to a quantity times its logarithm) in the list's length (<math display="inline">O(n\log n)</math>), but has a space requirement [[Proportionality (mathematics)|linear]] in the length of the list (<math display="inline">O(n)</math>). If large lists must be sorted at high speed for a given application, timsort is a better choice; however, if minimizing the [[memory footprint]] of the sorting is more important, bubble sort is a better choice.