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2.7: How asymptotic notation relates to analyzing complexity

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    49268
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    Temporal comparison is not the only issue in algorithms. There are space issues as well. Generally, a trade off between time and space is noticed in algorithms. Asymptotic notation empowers you to make that trade off. If you think of the amount of time and space your algorithm uses as a function of your data over time or space (time and space are usually analyzed separately), you can analyze how the time and space is handled when you introduce more data to your program.

    This is important in data structures because you want a structure that behaves efficiently as you increase the amount of data it handles. Keep in mind though that algorithms that are efficient with large amounts of data are not always simple and efficient for small amounts of data. So if you know you are working with only a small amount of data and you have concerns for speed and code space, a trade off can be made for a function that does not behave well for large amounts of data.


    This page titled 2.7: How asymptotic notation relates to analyzing complexity is shared under a CC BY-SA license and was authored, remixed, and/or curated by Wikibooks - Data Structures (Wikipedia) .

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