In functional programming,
combinator libraries refer to a design style that emphasizes bottom-up program construction.
Such libraries define a few core data types
and provide constructors—functions that create initial objects—and combinators—functions that build larger objects from smaller pieces.

Combinators enable the programmer to use intuitive visual and spatial reasoning
that’s vastly more powerful than linear language processing.
As a result, solving problems with combinators feels like playing with lego pieces.

Things we wish we didn't know

I just learned that
you can use it to review a git commit like this and I thought that was really
cool.

The share_target manifest member allows installed Progressive Web Apps (PWAs) to be registered as a share target in the system's share dialog.

This post is all about speculative compilation, or just speculation for short, in the context of the JavaScriptCore virtual machine.

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).

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

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.

Using systemd to avoid having to write some risky code

Aurora: An extensible, Python-based static site generator.

Comparison between types of API tokens.

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

From Erlang, to Elixir and now, GLEAM!?