Humble Pi: When Math Goes Wrong in the Real World

by Matt Parker

Some programmers had released a Chrome extension that people could download and use. To anonymously keep track of everyone who had installed it, upon installation it would generate a random number as an arbitrary user ID and send that back to the company’s database. They had a graph in the office showing a nice increase in installations of their extension until, one day, the number of new installs dropped to zero. Had the whole world suddenly decided to stop using their extension? Or was there some fatal flaw in their code that had caused it to stop working? No. Their extension was working fine, and people were still installing it. But it used the JavaScript programming language and called the built-in function Math.random() to get a new user ID number for each new install. This worked fine for the first few million cases but, from then on, it was returning only numbers that had already been used. This meant that all new users looked like duplicates of those already in the database. These user ID numbers were 256-bit values with possibilities measured in the quattuorvigintillions (around 1077). There is no way they should repeat so quickly. Something had gone wrong, and the MWC1616 algorithm was to blame. The pseudorandom numbers had looped. This was not the only case of Chrome users having random problems and, thankfully, the developers behind the browser’s JavaScript engine set about fixing the problem. As of 2016 Chrome has switched to an algorithm called xorshift128+ w...