Recently, Casey Muratori has implemented a proof-of-concept terminal, which is designed around fast input processing and rendering. This is an important and commendable effort, since the vast majority of software performs tens to thousands of times slower than it can.^{[citation needed]}

One of the design choices of refterm is to use a hash table to cache glyph rendering. The key in this table is the UTF-8 string of a single glyph. To avoid string allocations, the hash value of the glyph bytes is used as a key instead.

When Casey got asked about the possibility of hash collisions on stream, he responded with a claim that the hash function used in refterm is “a strong hash”, and the complexity to find collision is about 2^64 operations. After analyzing the code for the hash function used in refterm, a few flaws were found in the hash function, and O(1) attacks were discovered.

I wanted to know what data Oculus Runtime sends home. To do that, I’ve implemented a custom tool to extract TLS keys from a running Oculus Runtime instance.

You can find my findings below.

I want to be able to inspect the traffic of programs running on my computer. I don’t really trust those programs and ideally I’d like to put nearly all of them into a high security jail.

One of those programs is Oculus software. There are a few reasons why I want to be cautious about Oculus software.

This post is heavily inspired by Tom Stuart: Programming with noting, William Byrd on “The Most Beautiful Program Ever Written”, Guowei LV – The Most Beautiful Program Ever Written, John Tromp – Binary lambda calculus.

When I first learned about Lambda calculus, I was amazed by a strong mathematical basis for anonymous functions used in many languages.

Then I wondered: what’s the simplest way to represent lambda functions as data?

There is a beatiful web page: Monogatari drops, and it’s a rare example of an acceptable use of page scroll for artistic purposes.

The page is great, I like the concept, I like the art, I like monogatari series.

But there is a problem: the page is slow. And we’re going to fix it.

An optimized and fixed version of the page is available over here, and more details on the optimization process are available in the rest of this post.