I remember recently reading a new paper elaborating a novel presentation of graph algebras. But I can't for the life of me remember the title or the author.
The central idea was axiomatizing vertices as pairs of sets of all incoming and outgoing edges.
It also had example code in Haskell.
Does anybody have an idea of the title? I'd be very thankful for suggestions.
Finding Success (and Failure) in Haskell by Type Classes is on sale on Leanpub! Its suggested price is $35.00; get it for $12.50 with this coupon: https://leanpub.com/sh/4sG8LBPo#Haskell
@simon_brooke Hey buddy, checked out #Scheme/#Scsh yesterday, super intriguing stuff. Actually, I've been digging into #Lisp and its dialects lately. Got curious about why there are so many dialects, you know?
Recently dabbled in #Clojure, which got me looking at Lisp in a new light. Unlike #Haskell, which is awesome for sure, #Lisp has been out of academia and in the market for quite a while... found it pretty cool.
Here is a preprint of fun paper that I've been working on which investigates the utilization of formal descriptions of instruction semantics to perform symbolic binary-level program analysis: https://doi.org/10.48550/arXiv.2404.04132
It includes a prototype implementation in Haskell which performs symbolic execution of RISC-V binary code without requiring the transformation to an intermediate representation (like LLVM IR).
I'm currently finishing "The Heart of Salamanderland" for the Amstrad CPC, that will have a physical release by PolyPlay (see my Brick Rick for an example!).
The latest and greatest GHC version (9.8.2) is now available in the Alpine Linux Edge repositories and will be included in the upcoming 3.20 stable release.
Is there any future in languages like #haskell where AI makes code a factor of small frequently and easily replaced glue and scraps, where whatever is most trained on and most hackable, most easily replaced/iterable is king?
Are big pieces of software that benefit from the architectural assurances Haskell brings a dead paradigm?
AI is here to stay and I feel if something was not already in or out of orbit, it may never reach escape velocity
effectfully describes #Haskell as a beautiful and amazing language. In episode 46 of #TheHaskellInterlude, Wouter Swierstra and Joachim Breitner asked effectfully about how he found a new passion for programming. Listen to the episode here: https://haskell.foundation/podcast/46/
Compatible types across programming languages are also important.
What if you could easily make universal types across the languages in your stack, at the same time?
That's what I'm hoping to achieve with DataTypeTool. Still a very early product, but we're getting there. Currently producing valid (albeit not-yet-serializable) #elmlang#haskell and #gleam
You can always try out #haskell snippets on https://play.haskell.org! Many libraries, like aeson, containers, vector, effectful, text and text-builder-linear, are readily available!
@gregorni
Editor: #neovim or Pe
Multiplexer: still figuring out: only recently realised they're useful.
Package manager: #nixPackageManager / #haikuOS pkgman
Shell: bash (sometimes zsh, never got around to finding out the difference)
Language: #haskell, #rust, #rubylang, #cpp, whatever else tickles my fancy.
Containers: none (most recently docker)
Command runner: don't you mean shell?
Terminal emulator: the default ones from #CinnamonDesktop and #haikuOS