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Runtime & Spatial Complexity of the Code?


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  On 26/03/2015 at 01:08, Andre S. said:

That sounds like a homework question.

Hi Andre,

 

I am actually preparing for an interview. What I should have done is post the code I wrote and then shows what I think the complexity is and understand from experts here.

 

Sorry if it felt like one but it is not a homework question.

 

Thanks :)

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The complexity of an algorithm (in Big-O notation) is an upper bound on the growth rate of resources required to run it, expressed in terms of n where n is the number of elements. So it's a measure of how the algorithm scales as the problem size grows. For example, the growth in resources required to run an O(n^2) algorithm is no faster than the growth of the amount of elements squared.

 

Time complexity then refers to how much time is required to run the algorithm as a function of the number of elements. Space complexity refers to how much memory is required.

 

You can find this information explained in a variety of ways all around the web, for instance http://www.leda-tutorial.org/en/official/ch02s02s03.html

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