By Kardi Teknomo, PhD.

Analysis of Algorithm

Share this: Google+
| Next >

If you never heard the word big-oh notation before and want to know what is the meaning of it, this tutorial is for you. If you still think computer can solve all the computational problems, this short tutorial is also for you. By the end of this tutorial, you will know the important of analysis of algorithm, how to understand the meaning of computer jargon such as O(n^2) or O(log n), how to measure the running time of an algorithm, how to compare the efficiency of two algorithms and how to get the estimate of the running time (without the need to run the code) and how to rank the best, good and bad algorithms and how do we measure programmer's productivity that influence your IT cost.

Contents

Click the topics below.

Algorithm Motivating Story
Computational Complexity
Complexity Measures
Estimate Running Time
Best Algorithms based on Order of Complexity
Asymptotic Functions
Programmers’ Productivity

Rate & Comment this tutorial

 

Share and save this tutorial
Add to: Del.icio.us Add to: Digg Add to: StumbleUpon Add to: Reddit Add to: Slashdot Add to: Technorati Add to: Netscape Add to: Newsvine Add to: Mr. Wong Add to: Webnews Add to: Folkd Add to: Yigg Add to: Linkarena Add to: Simpy Add to: Furl Add to: Yahoo Add to: Google Add to: Blinklist Add to: Blogmarks Add to: Diigo Add to: Blinkbits Add to: Ma.Gnolia Information

These tutorial is copyrighted .

How to cite this tutorial:

Teknomo, Kardi. (2017) Analysis of Algorithm .
http://people.revoledu.com/kardi/tutorial/Algorithm/