I'm working on a new collaborative editing engine for arbitrary data, using CRDTs. I'm trying to keep it highly performant. (Like, 300M edits / second performant).

I've been working on this problem for years and I've gone through dozens of design revisions. Sometimes I catch bugs in the design phase. Sometimes I only notice core problems after I finish implementing parts then attach a fuzzer. (Fuzzy boi is the best and the worst.)

Some design problems have taken me months to find a solution. One of my solutions ended up with me rewriting of thousands of lines of working code, written over several months.

We're making great progress; but sync engines are hard.

Debugging is huge part of this. For example, for web where you can plop breakpoint or print statement anywhere and have a good level of transparency into what is happening really helps resolve issues quickly.

Game development where GPU is not really going spill the beans of what is happening under the hood that easily - one can stuck for a longer times easily.

I'm writing Swift code that calls Apple's UIKit. I'm constantly wasting time trying to figure out how to use the API properly, since it's buggy and poorly documented. Each solution brings relief, not euphoria.

Multithreading problems Algorithms problems where you have two variations of the algorithm that work for different combinations of inputs and you need it to work for both cases, so you need to merge the algorithms together. This is my most common programming experience. Realising how many problems a problem has, such as constraint satisfaction, layout engines and programming language design. Myers agorithm and diff3 See my profile for links to my GitHub profile to see what I'm working on.

Reducing latency. Or any sort of optimization for that matter. It’s usually a slow methodical process, but every once in a while you look at the right trace and instantly know what the problem is and how to fix it.