A collection of programming articles covering C++, Elm, Haskell, Kotlin, statistics, and software development concepts.
Dobiasd/articles is a collection of programming articles and tutorials written by a developer sharing insights on various programming languages, software development concepts, and practical coding examples. It serves as a personal knowledge repository covering topics from C++ and functional programming to statistics and refactoring techniques. The articles aim to document learnings and provide educational content for other developers.
Developers interested in functional programming concepts, language-specific tutorials (C++, Kotlin, Haskell, Elm), and software engineering best practices. It's particularly valuable for programmers looking for practical examples and clear explanations of complex topics.
This collection offers authentic, experience-based insights across multiple programming domains in one place. Unlike formal documentation or commercial tutorials, it provides personal perspectives and practical examples that help developers understand concepts through real-world applications and problem-solving approaches.
thoughts on programming
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Articles span C++, Elm, Haskell, Kotlin, and more, as shown in the README's categorized sections, offering insights across multiple programming paradigms.
Multiple articles explore functional concepts, such as 'From Object Oriented Programming to Functional Programming' and monad explanations, with practical applications in languages like C++ and Elm.
Includes real-world examples like HackerRank challenges and refactoring demonstrations in Kotlin, helping readers apply concepts directly to coding tasks.
Explains complex topics like covariance and async/await without code, making them accessible through analogies and first-principles explanations.
Described as a 'brain dump,' the articles are not structured for sequential learning, which can hinder systematic education and topic discovery.
All content is from one developer, limiting diversity of viewpoints and lacking peer review, which may introduce biases or unverified insights.
There's no indication of regular updates or versioning in the README, so articles on evolving topics like AI or libraries might become outdated.