It's also possible to use a slower "arbitrary PRNG and bump" scheme that tests the VRAM for the desired values(e.g. if it were a sprite, by running the blit at that pixel address and testing) and walks forwards or backwards until an unset value is found. If the walk can be done fast enough, it'll execute at the same framerate as an LFSR cycle-length fade. It can be further supplemented with an estimation heuristic or a low-resolution map to generate unique patterns. It's just less speedy and mathematically interesting to do that.

I haven't even checked to see if the final program uses it. It's the kind of thing, though, that you might go in thinking, "maybe I will need that", and it doesn't add too much overhead to your prototype.

* Write an initial mockup that exercises APIs and data paths in an imperative, mostly-straightline coding style

* Write a source code generator that reproduces part of the mockup by starting with the original code as a string and gradually reworking it into a smaller specification.

* Now maintain and extend the code generator, and write new mockup elements to develop features.

The mockup doesn't have to be 100% correct or clean, nor does the code generator have to be 100% clean itself, nor does 100% of the code have to be automated(as long as clear separation between hand-written modules and automatic ones exists), but the mockup is necessary as a skeleton to guide the initial development, and similar, comprehensible output one layer down is a design goal. Language-level macro systems are not typically sufficient for this task since they tend to obscure their resulting output, and thus become harder to debug. Languages that can deal well with strings and sum types, on the other hand, are golden as generator sources since they'll add another layer of checks.

I'm still only using this for personal code, but it's gradually becoming more "real" in my head as I pursue it: the thing that stopped me before was developing the right feedback loop, and I'm convinced that the way to go is with a pretty lean base implementation(Go is an example of how much language power I'd want to be using in the target output) and an assumption that you're building a bespoke generator for the application, that won't be used anywhere else.

Source code generation gets a bad rap because the immediate payoffs are rare, and it's easy to take an undisciplined approach that just emits unreadable boilerplate without gaining anything, but the potential benefits are huge and make me not really care about design patterns or frameworks or traditional "paradigms" anymore. Those don't achieve anywhere near the same amount of empowerment.

https://www.chess.com/blog/kurtgodden/the-longest-possible-c...

Chess AIs, perhaps needless to say, are very good at computing at the depth necessary to win drawn-out endgames.

And that's been true right from the beginning with Bitcoin: scams, schemes, heists, data loss - the headlines scream blood all the time. We've never had that kind of "mean time to disaster" in technology before. The status quo was that something would fail, but the failure would never quite get back to the individual or company that produced it. They would spin it away, and no careers would be harmed. But the likes of Solidity produces a meat-grinder, a blind destroyer of any who dare enter calling themselves rockstar.

I think it's kind of awesome and beautiful, in that sense. It will induce a maturation throughout the economy to adapt to this new pressure. But like adolescence, it can be an ugly work in progress, and I don't expect Ethereum itself to be a survivor at this rate.

If you really think something is wrong with it, post ideas for longer names that will clarify and not substantially impact density. I would probably conventionally use "n0" and "n1" instead of "m" and "n" to represent "n-1", "n" - but the usage he has is consistent throughout the file, which is more than I can say of my stuff sometimes.

[0] https://www.freepascal.org/docs-html/user/userse33.html

[1] https://www.freepascal.org/docs-html/prog/progch1.html#progs...

* Best-in-class compile times

* Modules; preprocessor is relevant, but not dominant

* Generics, variant records, function and operator overloads, exceptions, safe string and dynamic array types

* Libraries for common things, with a reasonably conventional style: APIs, containers, bindings, etc.

* No GC; pointers are available, but language features discourage casual usage. RAII pattern is achievable.

* Strong + static types, nominal types and type aliasing.

* Good IDE support, mature tooling, compiler has very broad platform support.

The new languages do win on a lot of the language-feature aspects(particularly memory safety when performing deep optimizations), but they don't have as good a story on the tooling. The compile speed is a major feature and is only likely to remain advantageous over time - and the features already in place are quite effective at limiting source code size, boilerplate, and dangerous constructs. This despite "Pascal is verbose" being memetic.

And if I want more high-level power, I've found that writing a FSM is the most probable path to achieving it. A FSM that embraces the problem domain is a tiny compiler: input source constructs, FSM checks them, applies appropriate algorithms, then emits a list of actions. More power? Add a second FSM to make it a two-pass compiler. Add a stack, or attach it to a database. If it has to be fast, it can generate code in the last step, too. Those things add tons of power to model the problem and aren't heavily dependent on language-side support.

So, like with every technology, there was some exuberance and overuse of a novel formalism which shows up in this paper: "scales to 100,000 threads", it proclaims. Not much later, interest in "green threading" and "lightweight concurrency" grew as a way to get some of the architectural benefits of being asynchronous while mitigating waste from large numbers of threads, and consensus shifted towards mixing the approaches, which seems to have converged on the few-threads, message-queue-per-thread approach.

So the people who are perceptually 10x tend to have hit on a strategy that keeps them in the feedback zone without being overly concerned about surfacing everything right this second, and have management that cooperate with their strategy.

However - shipping code is often very organic, cultivated stuff which foils attempts to establish a coherent philosophy, a through-line of "how it works" - it works because it worked the day before, all that changed was that a little bit more was added. Repeat till broken, then refactor back to sanity(else abandon ship). It's Sisyphean hill-climbing.

This in turn plays into the falsity of "engineering" as a way to describe what's going on with a lot of code. You can do it in the small, but at any scale the codebase habitually becomes a living organism. And that tends to get puzzle-solver types excited, because if it's alive and keeps changing, then they will have endless problems to solve forever!

So I believe the philosophers of the crowd ultimately tend to move away from the applications coalface and look for something relatively smaller that does allow some time for reflection and distillation of the problem.

It's very unfashionable advice in some circles, though. It sounds just enough like "go back to writing unstructured copy-paste spaghetti" to trigger some people's kneejerk. But the ground rules of "don't take subroutines, don't jump backwards" actually keep it from getting too far out of control, because they align you towards code that only uses enough flexibility for the task at hand, hence there's a lower likelihood of missing something. Very good practice for greenfield code where you might reflexively add a generalization that you don't use. I can still get better at it.

Edit: And one of the most important things it taught me, is that I can use scope blocks and a comment instead of a function, and it'll be sufficient.