A look into the world of random, and how the complete unpredictability of Twitch chat can be a part of it.
Lacking the time and desire to play video games as much as I used to, I often turn to Twitch — a streaming platform largely focussed on gaming — to satiate the part of me that still finds the hobby enthralling. Watching someone else play games on my behalf is a passive affair, requiring a lot less effort and dedication while still being exposed to some of the story, competition, and atmosphere that gripped me in my formative years.
Following on from part one to complete the DRBG using Twitch-entropy and start generating random numbers.
The GitHub repo for this project can be found at https://github.com/zaljubouri/twitch-rand.
In part one, we discussed what goes into making a real random number generator-we chose our entropy source, determined it to be poor, and decided to use it anyway. In this article, we’ll dig into the details of actually creating the generator. I’ve mentioned the National Institute of Standards and Technology (NIST) a couple of times already and I’m going to do so again, because they also provide documentation on creating a deterministic…
Multithreading can be complicated; here are three mistakes I made trying to incorporate it into a Node.js project using threads.js.
As part of my series on random number generation, I mentioned a suite of statistical tests used to determine whether a set of numbers is independent and identically distributed. I wrote these tests using Node.js and TypeScript — for convenience — without much thought given to performance and whether this approach was truly the best available to me.
A software developer living and working in London.