What does "input size" mean in algorithm analysis?

The number of algorithms being run

The amount of data the algorithm handles

In algorithm analysis, "input size" refers specifically to the amount of data that the algorithm is designed to handle. This can manifest in various forms depending on the problem being addressed—such as the number of elements in a list, the dimensions of a matrix, or the number of vertices and edges in a graph.

Understanding input size is crucial as it often directly impacts how efficiently an algorithm will perform. For instance, as the input size increases, the time or space requirements of the algorithm may also increase, which in turn helps in evaluating its scalability and efficiency.

The other options do not capture the meaning of input size accurately: the number of algorithms being run is unrelated to a single algorithm's input size, the complexity of the algorithm pertains to its inherent characteristics and performance rather than the quantity of data processed, and the maximum depth of recursion relates to specific algorithms that utilize recursion but does not define input size in general terms.

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The complexity of the algorithm itself

The maximum depth of recursion used

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