Comments on: Computer Algorithms: Interpolation Search

By: Vishal

Vishal — Fri, 15 Jun 2018 09:46:51 +0000

Good examlpe but if the result not found you need to keep running the loop but in the example you return -1 how loop continues to next stage.

By: Aneeta

Aneeta — Tue, 29 Aug 2017 04:16:02 +0000

interpolation search…that’s it..?i thought it was something that couldn’t be understood by a first time reader.but it felt quite simple. Thank you…

By: Princi the girl

Princi the girl — Thu, 27 Dec 2012 05:35:22 +0000

Very easy to understand. Although not enough deep drilling but good for first time reader. Graphical representations are always better than text.

By: Prince Rary

Prince Rary — Wed, 03 Oct 2012 11:06:49 +0000

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By: isha

isha — Sun, 16 Sep 2012 11:32:07 +0000

really nice 🙂 better dan wikipedia 😉 i love da diagrammatic description dat u gave

By: vipin

vipin — Sat, 15 Sep 2012 13:23:54 +0000

plz give aproof for its time complexity

By: Tudor Davies

Tudor Davies — Mon, 30 Apr 2012 10:23:32 +0000

Although what you're writing about is quite technical (probably an understatement), I found your description and diagrams quite easy to follow. About me: I’m a blogger for www.itrentals.com

By: Bystander

Bystander — Wed, 04 Jan 2012 08:17:54 +0000

You should be careful when you use the word “complexity”. It usually means “worst case” but not in this case.

To be more precise, interpolation search is O(n) as correctly noted by Ehud, but on average it behaves like O(log log n). This strongly depends on the distribution of your input, so interpolation is not always a better choice as O(n) is very slow.

On the other hand, binary search is always O(log n), whatever the input.

By: Ehud

Ehud — Mon, 02 Jan 2012 23:29:17 +0000

Hi, just a note – The interpolation search algorithm is O(log(log n)) only when the input is uniformly distributed.
In the worst case scenario the algorithm can cost up to O(n).