QuickCheck - Wikipedia

For decades, research in formal verification has been guided by a simple mental model that I recently coined the formal verification triangle. The triangle captures a trade-off between three desirable properties: Automation – the verification tool runs largely without human guidance Scalability – the technique works on large real systems Precision – the method can prove interesting properties, such as functional correctness Historically, verification techniques could reliably achieve two of the three, but not all three simultaneously.

How can we save time switching from one approach to another? Ideally everything would be decoupled and independent, right? Just hide it behind an interface!

Testing in Elm - Rogério Chaves

Efficient memorization using the spacing effect: literature review of widespread applicability, tips on use & what it’s good for.

A messy, real-life example E2E test case for an API I'm working on

A collection of examples of how to use Common Lisp

Efficient memorization using the spacing effect: literature review of widespread applicability, tips on use & what it’s good for.

Testing software-intensive systems involves more decisions than the standard vocabulary suggests. The conventional taxonomy (unit, integration, system, …

Bugs are a tricky subject. We all write code with bugs and they have a considerable impact on our productivity and on the value added by our deliverables. So we come up with several strategies to handle the bug stream and have a ongoing effort to balance bug house keeping and new features. I’m a big advocate for a zero bug policy. This means that we should usually have 0 registered bugs. Whenever I present this idea I’m met with skepticism. This is seen as an utopia and not possible. My impression is that developers interpret in a way that would generate punishment when new bugs are added. But that is not the point. The point is to embrace that we’ll always have bugs, but also aim for a process that will minimize as much as possible the amount of bugs we produce. This will make us leave our comfort zone and question our beliefs. It’s not about “writing code that never has bugs”. It’s more about “what do we need to change in our day to day work to minimize bugs”.

It’s hard to compete with Haskell’s QuickCheck when it comes to having random test cases generated for you from properties. QuickCheck in Haskell is aided by …

Efficient memorization using the spacing effect: literature review of widespread applicability, tips on use & what it’s good for.

Academic communities have increased the reach and accessibility of their work by publishing interactive, open-access, open-source articles on the web that explain both core and emerging ideas in th…

My approach to the Roman Numerals Kata

Or: How I Got Blindsided By Syntax

Chris James, London - Software Engineer

This is a blog version of a talk that I did ~2015 in Auckland. Nothing in it is original or unknown, but there aren’t that many examples of doing this aside from in the FsCheck documentation. I also gave a talk which contains a very similar example to the Melbourne ALT.NET meetup in 2018. What is FsCheck? FsCheck is a library in the spirit of Haskell’s QuickCheck, which allows you to perform property-based testing. The main feature that it provides is the ability to generate arbitrary instances of any supported data type, and the ability to define your own generators.

Author: Igor Konnov

Efficient memorization using the spacing effect: literature review of widespread applicability, tips on use & what it’s good for.

How we verify correctness

Code review is about more than checking for mistakes; it is about ensuring simplicity.

I saw this Mastodon post from Andy Wingo recently: in these days of coding agents and what-not, i often think of gerald sussman's comm...

Way back in December, in the spirit of the times (it seems that everyone was either solving Advent of Code or looking for a job), like an elephant in a china shop, I found myself solving a…

Including an example of property-based testing without much partitioning.

Outwitting malicious compliance with property-based testing

A jargon-free, practical explanation of monads as a design pattern.