In this episode, I explore the notion of fit and how it is missing from the Stratified Design paper.
Thoughts on Functional Programming Podcast
An off-the-cuff stream of Functional Programming ideas, skills, patterns, and news from Functional Programming expert Eric Normand.
In this episode, I read and comment on excerpts from John McCarthy’s 1971 Turing Award Lecture.
In this episode, I read and comment on an excerpt from the 1970 Turing Award Lecture by James Wilkinson.
When using the onion architecture, you need to consider the dependencies (actions depend on calculations), but also you need to consider the semantic dependencies (the domain should not know about the database).
Functional programming is a mindset that distinguishes actions, calculations, and data. That’s where it derives its power. Simply applying the discipline of ‘only pure functions’ lets you programming using a procedural mindset and still think you’re doing functional programming.
Force is an important concept in Newtonian mechanics. But do forces really exist? In fact, it is an abstraction invented by Newton. The insight revolutionized physics and universalized his model. What can we learn from it?
One of the greatest domain models ever built was Newtonian mechanics. Why did it take physics, as a field, thousands of years to figure it out? What can we learn from Newtonian mechanics to help us model our own domains?
We discuss two phases of domain modeling, one easy and one difficult.
If design is a false nominalization, then we should look at the process of design instead of pontificating on what makes good design.