from Hacker News

A Gentle Introduction to Algorithm Complexity Analysis (2012)

by epenn on 2/22/15, 6:56 PM with 7 comments

  • by tlarkworthy on 2/22/15, 10:20 PM

    A handy tip to reverse engineer complexity from empirical examples is plot on a log-log plot and measure the gradient (if its a straight line). The gradient is the exponent, ie. O(n^gradient). Great if your algorithm is so complex you can't analyze it.

    http://www.dgp.toronto.edu/people/JamesStewart/378notes/05lo...

  • by men on 2/22/15, 8:52 PM

    Very nice resource to have in mind. Thanks. I just started reading SICP. Decided to take a short detour to get a better grasp on all this complexity stuff that's hardly elaborated in SICP. Right now I am working through the chapter on Algorithm Efficiency Analysis in Discrete Math and Applications by Susanna Epp.

  • by mholt on 2/22/15, 11:38 PM

    Well, I appreciate that the article is easier to read than most textbooks on the subject. (But for as long as it is, it really is just an introduction - scrapes the surface.)

    Also, what's up with the random pictures in the comments?

  • by shobhitverma on 2/23/15, 4:30 PM

    Which problem is more important a) Make simple algorithms more accessible to the masses who do not get it even after reading a book. OR b) Make more complex algorithms and programming patters/styles more accessible to the good programmers who want to become excellent programmers ? I would like your opinion and how you define "importance" ( it could be market size, or economic impact in the world, or as some people have argued -- reduces gender inequality in tech)

  • by muyuu on 2/22/15, 11:39 PM

    What's with the pics in the comments? I'm a bit confused. Is this something about that site?