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.

Extra is different than More. Extra is finishing those two screens, but then researching a new library for form validation that might reduce the boilerplate code. Or it's learning ways to protect against common security vulnerabilities from data entry. These little off-ramps from the main highway of Normal Work could be dead-ends and not have any practical value to the project. But they might also be important contributions. And that's the thing with Extra. While the tangible value to the project is uncertain (it could be nothing this time or it could be something), the value to you is real.

Games can be made in many different ways. Many games are made using big, general purpose game engines such as Unity and Godot. I enjoy using the Odin Programming Language combined with Raylib.
Odin is a C-like programming language and Raylib is library for drawing graphics, checking input and playing sounds. So it’s just a program that uses a simple library, no engine!
There are no objectively best ways to create games.

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

I recently wrote about Async Pool, one of my favorite JavaScript / TypeScript helpers, and today I want to share an even simpler yet extremely useful utility

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

A fun, hands-on guide to writing your own compiler for a real-world programming language.

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

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.

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.

Most programming language ecosystems provide assert functions in their testing libraries but not Go's. Go's standard testing package follows a more direct and to-the-point approach.

piku, inspired by dokku, allows you do git push deployments to your own servers, no matter how small they are.