I started writing this post because, for whatever reason, I keep forgetting what the difference is between a ring and a group, which is funny to me because I never forget the difference between a semiring and a semigroup – although other people do, because it’s quite easy to forget! So, I wanted a fast reference to the kinds of algebraic structures that I am most often dealing with in one way or another, usually because I’m writing Haskell (which has some reliance on terminology and structure from abstract algebra and category theory) or I’m trying to read a book about category theory and they keep talking about “groups.” Wikipedia, of course, defines all these structures, and that’s fine, but what I need in those times is more of a refresher than an in-depth explanation.

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.

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! ⚡

The expression problem describes how most types can easily be extended with new ways to produce the type or new ways to consume the type, but not both. When abstract syntax trees are defined as an algebraic data type, for example, they can easily be extended with new consumers, such as print or eval, but adding a new constructor requires the modification of all existing pattern matches. The expression problem is one way to elucidate the difference between functional or data-oriented programs (easily extendable by new consumers) and object-oriented programs (easily extendable by new producers). This difference between programs which are extensible by new producers or new consumers also exists for dependently typed programming, but with one core difference: Dependently-typed programming almost exclusively follows the functional programming model and not the object-oriented model, which leaves an interesting space in the programming language landscape unexplored. In this paper, we explore the field of dependently-typed object-oriented programming by deriving it from first principles using the principle of duality. That is, we do not extend an existing object-oriented formalism with dependent types in an ad-hoc fashion, but instead start from a familiar data-oriented language and derive its dual fragment by the systematic use of defunctionalization and refunctionalization. Our central contribution is a dependently typed calculus which contains two dual language fragments. We provide type- and semantics-preserving transformations between these two language fragments: defunctionalization and refunctionalization. We have implemented this language and these transformations and use this implementation to explain the various ways in which constructions in dependently typed programming can be explained as special instances of the phenomenon of duality.

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

This article presents the program earlyoom to prevent a Linux system to lock up in low memory situations.

There’s plenty of information out there on how to scale Django to handle numerous requests per second, but most of it…

Last year I finally decided to learn some Rust. The official book by Steve Klabnik and Carol Nichols is excellent, but even after reading it and working on some small code exercises, I felt that I …

Go programming language is known to be easy to use. Thanks to its well-thought syntax, features and tooling, Go allows writing easy-to-read…

Hard disagree on this one, but still interesting.