Overhead (computing)

In computer science, overhead is any combination of excess or indirect computation time, memory, bandwidth, or other resources that are required to attain a particular goal. It is a special case of engineering overhead.

A programmer/software engineer may have a choice of several algorithms, encodings, data types or data structures, each of which have known characteristics. When choosing among them, their respective overhead should also be considered.

In software engineering, overhead can influence the decision whether or not to include features in new products, or indeed whether to fix bugs. A feature that has a high overhead may not be included – or needs a big financial incentive to do so. Often, even though software providers are well aware of bugs in their products, the payoff of fixing them is not worth the reward, because of the overhead.

For example, an implicit data structure or succinct data structure may provide low space overhead, but at the cost of slow performance (space/time tradeoff).

Algorithmic complexity is generally specified using Big O Notation. This makes no comment on how long something takes to run or how much memory it uses, but how its increase depends on the size of the input. Overhead is deliberately not part of this calculation, since it varies from one machine to another, whereas the fundamental running time of an algorithm does not.

This should be contrasted with algorithmic efficiency, which takes into account all kinds of resources – a combination (though not a trivial one) of complexity and overhead.

Invoking a function introduces a small run-time overhead. Sometimes the compiler can minimize this overhead by inlining some of these function calls.

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