alt Hacker NewsBy complete coincidence, yesterday I came across this link to an article Peter Naur wrote in 1985 (https://pages.cs.wisc.edu/~remzi/Naur.pdf) which I haven't been able to stop thinking about.
I've been doing this for coming up on thirty years now, mostly at one large company, and I spent a significant number of hours every week fielding questions from people who are newer at it who are having trouble with one thing or another. Often I can tell immediately from the question that the root of the problem is that their world model (Naur would call it their Theory) is incomplete or distorted in some way that makes it difficult for them to reason about fixing the problem. Often they will complain that documentation is inadequate or missing, or that we don't do it the way everyone else does, or whatever, and there's almost always some truth to that.
The challenge then is to find a way to represent your own theory of whatever the thing is into some kind of symbolic representation, usually some combination of text and diagrams which, shown to a person of reasonable experience and intelligence, would conjure up a mental model in the reader which is similar to your own. In other words you want to install your theory into the mind of another person.
A theory of the type Naur describes can't be transplanted directly, but I think my job as a senior developer is to draw upon my experience, whether it was in the lecture hall or on the job, to figure out a way of reproducing those theories. That's one of the reasons why communication skills are so critical, but its not just that; a person also needs to experience this process of receiving a theory of operation from another person many times over to develop instincts about how to do it effectively. Then we have to refine those intuitions into repeatable processes, whether its writing documents, holding classes, etc.
This has become the most rewarding part of my work, and a large part of why I'm not eager to retire yet as long as I feel I'm performing this function in a meaningful way. I still have a great deal to learn about it, but I think that Naur's conception of what is actually going on here makes it a lot more clear the role that senior engineers can play in the long term function of software companies if its something they enjoy doing.
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Regarding the tension between symbolic representation and Naur "theory", I'd actually say they come from two different traditions, each providing two different theses. When writing them out I think it becomes a bit clearer how they interact and that they're not actually contradictory.
Thesis A is something like: the value of the programmer comes from their practical ability to keep developing the codebase. This ability is specific to the codebase. It can only be obtained through practice with that codebase, and can't be transferred through artefacts, for the same reason you can't learn to play tennis by reading about it (a "Mary's Room" argument).
This ability is what Naur calls "theory". I think the term is a bit confusing (to me, the word is associated with "theoretical" and therefore to things that can be written down). I feel like in modern discourse we would usually refer to this as a "mental model", a "capability", or "tacit knowledge".
Then there's Thesis B, which comes more from a DDD lineage, and which is something like: the development of a codebase requires accumulation of specific insights, specific clarifying perspectives about problem-domain knowledge. The ability for programmers to build understanding is tied to how well these insights are expressed as artefacts (codebase structure, documentation, communication documents).
I feel like some disagreements in SWE discourse come from not balancing these two perspectives. They're actually not contradictory at all and the result of them is pretty common-sensical. Thesis A explains the actual mechanism for Thesis B, which is that providing scaffolding for someone learning the codebase obviously helps, and vice-versa, because the learned mental model is an internally structured representation that can, with work, be externalised (this work is what "communication skills" are).
It's interesting that the way you describe it, the world model itself is _not_ just a collection of words in our minds, and I have a small theory of my own that "thoughts" in our brains aren't actually words at all (otherwise animals which don't talk wouldn't be able to make complex decisions?), and the words that we "hear" in our heads and which we perceive as our thoughts are just a rough translation of these thoughts into words, they aren't thoughts themselves. It is also why it's sometimes really hard to put complex (but correct) thoughts into words, and especially hard to adequately compare complex ideas during a regular conversation: on the surface a lot of ideas (especially in software engineering) "sound" good, but they're actually terrible. And there's no better way to communicate ideas than to put them into words, which is probably what makes good software engineering extremely difficult.
Or maybe I'm just a little bit insane. Or both.
Obligatory link to a great podcast that has a great episode covering this paper: https://pca.st/episode/dfc024c8-31f8-4387-b301-7a4f77132b74
Everyone should subscribe to the Future of Coding (recently renamed to the Feeling of Computing) podcast if you haven't already: https://feelingof.com/
I keep saying this is the single most important article to consider when talking about AI assisted software building. Everyone should read it. The question should always be: is a human building a theory of the software, or is does only AI understand it? If it's the latter, it is certainly slop.
(Second, albeit more theoretical, would be A Critique of Cybernetics by Jonas)
>their world model (Naur would call it their Theory) is incomplete or distorted in some way that makes it difficult for them to reason about fixing the problem
Of course the model is incomplete compared to reality. That's in the definition of a model, isn't it? And what is deemed a problem in one perspective might be conceived as a non problem in an other, and be unrepresentable in an other.
Isn't that interesting? The job of exploring a theory or model to such an extent that it can be expressed in computer code always seems to fall on the shoulders of a software developer. Other people can write specifications and requirements all day long, but until a software developer has tackled the problem, the theory probably hasn't been explored well enough yet to express clearly in computer code. It feels like software developers are scientists who study their customers' knowledge domains.