3 ms·

> Don’t get confused between using smaller keywords and actually understanding the problem at hand. Absolutely. I'm not arguing for maximal terseness and spent

> Don’t get confused between using smaller keywords and actually understanding the problem at hand. Absolutely. I'm not arguing for maximal terseness and spent a lot of words attempting to say otherwise. (IMHO, we're both reflexively reacting to our parent comments a bit). What I am wanting to point out is that form affects function and how we think about and use our languages. This in turn shapes our ecosystems and cultures, which influence our heuristics for keeping a pulse on project health and the surrounding support structures. Which all in turn reflect back to affect the forms we like and produce! The mechanics of middle-sized and large businesses naturally incentivize bloat and churn to some degree, not because we necessarily want those things, but because coordination and communication are large information bottlenecks, a la Mel Conway's observations [0]. When our heads are filled with syntax, tooling, best practices, and absolute ideas about what correct code looks like, we make it that much harder to fill our heads with direct problem-domain concerns. While senior engineers can and often do successfully wade through all that, it's a long grind, and anything that empowers team members to get there faster seems like an obvious win. I wish that we as a community could better recognize that our values like "semantics over syntax" or "code review is necessary" or "readability is good" implicitly invoke a large set of contingencies in order to become heuristics that serve well. Tools that violate our common sense and aesthetic values present an opportunity to sanity check those sentiments and potentially sharpen our understanding of them. In my experience, APL and probably K are really excellent at that, offering a new way of thinking that highlights clear disfunctionalities within our current "mainstream" languages and cultures. If true, isn't that something we obviously want to eagerly investigate? So, to bring it back, I think the statement that "AST node count is a better" embodies exactly the kind of values and mindset that make it harder for us to grow. What do we think about readable, maintainable, highly terse code? Does this K sample exemplify that? Why are K and APL successfully (if quietly) running significant portions of our economy? What structural, organizational, and cultural lessons do they embody that we can learn from? [0]:http://www.melconway.com/Home/Committees_Paper.html http://www.melconway.com/Home/Committees_Paper.html

dahart 2y ago
I don’t know what you mean, and currently do not agree with the idea of parse tree size being a bad mentality or making it harder to grow, and I don’t feel like you’ve provided any objective evidence to back up that claim. Parse tree size seems like a better metric than terseness, for the reasons I and others have already mentioned, despite the fact that sometimes tight small code has some advantages that might be invisible if your only metric is AST size. (Neither parent nor I made such a claim, but your argument depends on that assumption.) K specifically is unreadable by most people, and somehow examples never seem to come with comments or error handling. Is it the best poster child for programming progress as a whole? I have my doubts, even though it might be very useful for some people in some situations. I would be willing to bet that Excel spreadsheets are running more of our economy than K code, likely by orders of magnitude. I’d also be willing to bet that COBOL exceeds K use by similar multiples. Business/economic use doesn’t seem like a very good metric for what you’re talking about.
- xelxebar 2y ago
  The original post I replied to made an explicit claim with zero evidentiary support, so your demands for rigor are a bit lopsided. But more to the point, I'm really not saying anything about which metric is better or whatnot. What does it even mean to be a "better metric" when we have no consensus on what criteria we're using for comparison? In effect, replies here effect to provide some criteria, but each is slightly different and somewhat begs the question, since said criteria can be easily chosen to support whatever conclusion you want. When the object level discussion (i.e. in this case, the comparison of code size metrics) is ill-defined, the only natural thing we can reach for are cached ideas, heuristics, memetic trends, etc. That is, the discussion essentially becomes an implicit sharing of which cultural ideas we consider salient and important. That is why I keep going on about culture and values in my previous replies. I'm not saying anything about ASTs vs. token count or whatever. I'm trying to say, "Hey, fellow devs. You know all the obvious ways that K and APL violate our sense of what good and proper code should look like? You know how they feel wrong? Well, actual experience by APL and K devs provides us evidence that we're potentially wrong and should give these languages more open-minded attention."
  - 2y ago

dahart 2y ago

I don’t know what you mean, and currently do not agree with the idea of parse tree size being a bad mentality or making it harder to grow, and I don’t feel like you’ve provided any objective evidence to back up that claim. Parse tree size seems like a better metric than terseness, for the reasons I and others have already mentioned, despite the fact that sometimes tight small code has some advantages that might be invisible if your only metric is AST size. (Neither parent nor I made such a claim, but your argument depends on that assumption.) K specifically is unreadable by most people, and somehow examples never seem to come with comments or error handling. Is it the best poster child for programming progress as a whole? I have my doubts, even though it might be very useful for some people in some situations. I would be willing to bet that Excel spreadsheets are running more of our economy than K code, likely by orders of magnitude. I’d also be willing to bet that COBOL exceeds K use by similar multiples. Business/economic use doesn’t seem like a very good metric for what you’re talking about.

xelxebar 2y ago
The original post I replied to made an explicit claim with zero evidentiary support, so your demands for rigor are a bit lopsided. But more to the point, I'm really not saying anything about which metric is better or whatnot. What does it even mean to be a "better metric" when we have no consensus on what criteria we're using for comparison? In effect, replies here effect to provide some criteria, but each is slightly different and somewhat begs the question, since said criteria can be easily chosen to support whatever conclusion you want. When the object level discussion (i.e. in this case, the comparison of code size metrics) is ill-defined, the only natural thing we can reach for are cached ideas, heuristics, memetic trends, etc. That is, the discussion essentially becomes an implicit sharing of which cultural ideas we consider salient and important. That is why I keep going on about culture and values in my previous replies. I'm not saying anything about ASTs vs. token count or whatever. I'm trying to say, "Hey, fellow devs. You know all the obvious ways that K and APL violate our sense of what good and proper code should look like? You know how they feel wrong? Well, actual experience by APL and K devs provides us evidence that we're potentially wrong and should give these languages more open-minded attention."
- 2y ago