I feel uneasy about design patterns.
On the one hand, my university class on design patterns revived my interest in programming.
On the other hand, I find most patterns in the Gang of Four book to be irrelevant to my daily work;
they solve problems that a choice of programming language or paradigm creates.

My litmus test of a good design pattern is its cross-disciplinary applicability.
I’m more likely to accept an idea that pops up in fields beyond software engineering.
And the most convincing patterns are the ones that help me in everyday life.

This article describes a universal pattern that billions of people rely on daily, but software engineers rarely discuss—the plan-execute pattern.

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

Solving AoC on the DS with Rust.

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

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

Code discussions contain relevant information. Isn’t it a shame that we
keep these in the centralized GitHub/GitLab servers, far away from our
decentralized Git code? As soon as we move provider, we’ll lose all old
discussions! And how do you ever find the pull requests back from 5
years ago? Symfony has implemented a lightweight solution to this problem
years ago using a less-known feature of Git: Git Notes.

I’ve used a lot of tools over the years, which means I’ve seen a lot of tools hit a plateau. That’s not always a problem; sometimes …

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.

Sales pitches are the only place where “self-serve dashboards" work. In the real world, it's a different story.

Why "business" people don't use metabase/power-bi.

I've been running NetBSD on a RockPro64 since NetBSD 10-BETA, and I'm still happy with it now with NetBSD 10-RELEASE. I'm always looking for hardware to hack NetBSD though, and I recently watched a FOSDEM 2024 video: NetBSD 10: Thirty years, still going strong!. The Pinebook Pro laptop was mentioned at one point, which has the same RockChip SoC as the RockPro64. That reminded me I'd been wanting to give this inexpensive ARM 64 laptop a try.