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.

I have a lot of thoughts about the design of compiler intermediate representations (IRs). In this post I’m going to try and communicate some of those ideas and why I think they are important.

There are a lot of guides about how to use async Rust from a "user's
perspective", but I think it's also worth understanding how it
works, what those async blocks actually mean.

Every so often I come across a paper, blog post, or (occasionally) video that completely changes how I think about a topic in programming languages and compilers. For some of these posts, I can’t even remember how I thought about the idea before reading it—it was that impactful.

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

Everything you need to write flexible, future-proof Rust applications using hexagonal architecture.

A lightning post on logic programming in Haskell to construct a workout weekly schedule given the set of exercises, days and constraints.

plainweb is a framework using HTMX, SQLite and TypeScript for less complexity and more joy.

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.

Between our ESP32 prokaryotic organisms and our 24/7 Internet-enabled megafauna servers, there exists a vast and loosely-defined ecosystem of things the B2B world likes to call computer appliances. Picture a bespoke Pi 4 packaged up neatly with some Python scripts, a little fancy plastic embossing, and maybe a well-guarded id_ed25519.pub in case you end up in hot water during the (long - very long, stable cash flow for generations long) maintenance contract, and you’re in the ballpark.

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.