An overview of what makes modern CSS so awesome.

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.

This web app displays notes and slides in separate windows,
keeping both synchronised.
It accepts simple, double-width, or double-height PDF presentations:

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.

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.

Interesting setup for pet computers. Debian + sway + cage

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.

Living specification of the IRC protocol. Does not include brand new behavior, just existing behavior present in IRC software and/or networks (new extensions are IRCv3's area).