Big Oh notation only gives the proportionality of the time required for that particular algorithm.
For an approximation you can assume some hypothetical machine and calculate the time taken using the costs for loads,stores,etc. And you can also find the total time for execution using the platform specific "time" commands. This gives a good comparison bet the expected and practical timings. But it is imp to note that in the practical timings the lower order terms also come into play for the complexity proportionality, hence the expexted and practical times mostly vary a bit. On 11/22/07, Sherry <[EMAIL PROTECTED]> wrote: > > > I know how the complexity of an algorithms is calculated, but how > would this relate to the time it takes? Let's say I have 25000 random > numbers I'd like to sort with the selection sort. Now how could I use > Big O notation to calculate the time taken to sort these numbers?? I > mean I understand it's a O(n^2) sort, but how do you approximate time > taken?? > > Thanks in advance. > > > -- Ciao, Ajinkya --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Algorithm Geeks" group. To post to this group, send email to algogeeks@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/algogeeks -~----------~----~----~----~------~----~------~--~---
