# Dobiasd/articles

thoughts on programming

Repository: https://github.com/Dobiasd/articles
Canonical: https://ross.abutalabs.com/products/dobiasd-articles
Language: Python
License Family: other
Topics: functional-programming, articles, blog
Last push: 2026-01-01T15:39:53+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 60, release rhythm 35, longevity 100
- inputs: {"age_days": 4683, "days_push": 244, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1587, forks 91 (observed 2026-08-28T04:05:07.910473+00:00)

## What it is
A collection of programming-related articles by Dobiasd, covering topics like functional programming in C++, Haskell, Kotlin, Elm, and statistics. It serves as a personal blog/brain dump hosted on GitHub.

## Use cases
- learn functional programming concepts in C++
- understand the expression problem in Haskell
- read about refactoring examples in Kotlin
- learn basic descriptive statistics
- compare programming language learning curves

## When to choose
- you want readable articles on functional programming across multiple languages
- you are interested in practical statistics and A/B testing explanations
- you enjoy blog-style deep dives into language features

## When to avoid
- you need runnable software or a library
- you need a single-topic structured tutorial or course
- you need content under an explicit open-source license

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: programming-languages, tutorials, developer-tools
- platform: -
- tags: blog, articles, functional-programming, cpp, haskell, kotlin, elm, statistics

## Member repositories
- Dobiasd/articles (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:07.910473+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:55:06.288385+00:00, confidence not recorded.
  - readme: https://github.com/Dobiasd/articles (fetched 2026-08-28T04:05:07.910473+00:00, sha e1ce6e5a5336)
- Data as of 2026-08-30T08:39:29.467469+00:00.