An overview of what makes modern CSS so awesome.

We recently ran across a strange higgs-bugson that manifested itself in a critical system that stores and distributes the firm’s trading activity data, called Gord. (A higgs-bugson is a bug that is reported in practice but difficult to reproduce, named for the Higgs boson, a particle which was theorized in the 1960s but only found in 2013.) In this post I’ll walk you through the process I took to debug it. I tried to write down relevant details as they came up, so see if you can guess what the bug is while reading along.

zb is a tool for reproducibly building software, similar to Bazel.
(See the comparison page if you’re curious to know the differences.)
When a software build process is reproducible,
it will produce the exact same output
when given the same inputs.
Reproducibility is a desirable property for a software build process to have:
it simplifies debugging,
it enables build speed-ups,
and it is essential for digital supply chain security.
However, reproducibility is a difficult goal to achieve.

I have been using IntelliJ Idea at work for a decade or so by now, and it’s been a reliable companion. JetBrains IDEs have a bit of a reputation for being slow, but their feature set is incredible: powerful refactoring tools, a great VCS UI (though I like magit even more!), a huge number of supported frameworks, integration with just about any testing library for any language, code coverage tools, powerful debuggers, etc.

Reading through the Emacs 30 NEWS file and picking
out the stuff I think is the most interesting.

Security testing starts with understanding vulnerabilities. The CVE website lists known software flaws. The OWASP Top Ten highlights common weaknesses. With this knowledge, we can improve our Go development. This article shows how to put in place robust practices. They are to: fuzz inputs, verify dependencies, and use static analysis tools (SAST).

useDeferredValue is one of the most underrated React hooks. It allows us to dramatically improve the performance of our applications in certain contexts. I recently used it to solve a gnarly performance problem on this blog, and in this tutorial, I'll show you how! ⚡

There's a concept that I've heard called by a lot of different names, but my favorite name for it is …

Most functional languages rely on some garbage collection for automatic memory management. They usually eschew reference counting in favor of a tracing garbage collector, which has less bookkeeping overhead at runtime. On the other hand, having an exact reference count of each value can enable optimizations, such as destructive updates. We explore these optimization opportunities in the context of an eager, purely functional programming language. We propose a new mechanism for efficiently reclaiming memory used by nonshared values, reducing stress on the global memory allocator. We describe an approach for minimizing the number of reference counts updates using borrowed references and a heuristic for automatically inferring borrow annotations. We implemented all these techniques in a new compiler for an eager and purely functional programming language with support for multi-threading. Our preliminary experimental results demonstrate our approach is competitive and often outperforms state-of-the-art compilers.

In this post, I talk about pleasant but seemingly minor features in personal sites

Official website of the Pimalaya project.

A single-user “wiki” engine powering the ThoughtStorms wiki.