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2. Complexity is Bad—as a Concept (jelv.is)

I don't like talking about “compelxity” in software any more. People have radically different ideas of what “complexity” means, and “complexity” conflates several inherently distinct concepts.

3. Letting Experts Be Experts (jelv.is)

Experts aren't just beginners with more knowledge, they operate in a fundamentally different way. How can we empower rather than hinder them?

4. By Looking (jelv.is)

Years ago, I heard a stupid philosophy joke: a student taking an intro philosophy class asks the professor “but how do we know?”; then, when the professor gives an answer, the student asks “okay, but how do we know that?” This keeps on going until eventually the professor gets fed up and says “by lo...

5. Three Regimes for Resilience (jelv.is)

A useful mental tool for designing resilient software: consider how the system will operate in three separate regimes: The happy path. Everything is handled automatically with no manual intervention needed. Small issues crop up requiring narrowly scoped—but not necessarily routine—human intervention...

6. Debugging Haskell Type Errors (jelv.is)

Fixing Haskell type errors can be hard. Learning how to understand and fix type errors was the first real obstacle I faced when I first picked up the language. I’ve seen the same tendency with every Haskell beginner I’ve taught. With a bit of experience, I got so used to the quirks of GHC’s typechec...

7. Structure your Errors (jelv.is)

Recently, I’ve revisited how I represent errors in code. I’m working on a command-line tool used across multiple teams and I want to keep its error messages consistent and readable. As the codebase has grown, I’ve moved from ad hoc error strings throughout my code to a structured error type. I never...

8. Haskell, Monads and Purity (jelv.is)

I believe the notion that Haskell uses “monads” to enforce purity is rather misleading. It has certainly caused quite a bit of confusion! It’s very much like saying we use “rings to do arithmetic”. We don’t! We use numbers, which just happen to form a ring with arithmetic operations. The important i...

9. Lazy Dynamic Programming (jelv.is)

Dynamic programming is a method for efficiently solving complex problems with overlapping subproblems, covered in any introductory algorithms course. It is usually presented in a staunchly imperative manner, explicitly reading from and modifying a mutable array—a method that doesn’t neatly translate...

10. Generating Mazes with Inductive Graphs (jelv.is)

A few years ago—back in high school—I spent a little while writing programs to automatically generate mazes. It was a fun exercise and helped me come to grips with recursion: the first time I implemented it (in Java), I couldn’t get the recursive version to work properly so ended up using a while lo...
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