These pages show 8 different sorting algorithms on 4 different initial conditions. These visualizations are intended to:

• Show how each algorithm operates.
• Show that there is no best sorting algorithm.
• Show the advantages and disadvantages of each algorithm.
• Show that worse-case asymptotic behavior is not the deciding factor in choosing an algorithm.
• Show that the initial condition (input order and key distribution) affects performance as much as the algorithm choice.

This website is an experiment that uses Color Theory to randomly select a color scheme that is supposed to look nice with every refresh.

Second part of the very good article about having more data vs. better algorithms

The graph-based SPEAR algorithm (Spamming-resistant Expertise Analysis and Ranking) is a new technique to measure the expertise of users by analyzing their activities. The focus is on the ability of users to find new, high quality information in the Internet. At the same time, the algorithm has been shown to be very resistant to spamming attacks.

Bubble Sort; Insertion Sort; Median-of-three Quicksort; Multiple Link List Sort; Shell Sort

Randomly choosing colors that look good.

This page has visualizations of some comparison based sorting algorithms.

Problèmes d’algorithmique et leurs implémentations en Caml

Very interesting thoughts about the fact that sometimes it pays more to add more data rather than fine-tuning the weights on your fancy machine-learning algorithm.

This seems to be to the social web what PageRank is to the classic web.