I disagree about Bret Victor. There is nothing simple about the principles that he uses. In fact you need a whole lot of very deep theoretical understanding to even get to the point of Bret's abilities. Time traveling debuggers for one are very advanced technology. If anything Bret Victor is applying very advanced theory to mundane domains like programming.
> Time traveling debuggers for one are very advanced technology.
Yes they are. But the underlying principles are dead simple: just keep all the history of the memory, never erase anything!
Of course, the implementation is not that simple, because efficiency, because complex imperative languages, because many other things. But the basic principles are still dead simple. You may be amazed by time travelling with GDB, but OCaml had that years before GNU did it.
I feel the same way about Bret Victor. He does understand things that are hard to grok. Probably very abstract stuff. But I suspect it wouldn't take much space to write those things down.
I gather you have seen his videos, most notably the dead fish and dynamic visualization ones? Learnable Programming also counts. Tell, me, why did you find those presentations so amazing?
The reason I found them so amazing was their simplicity. Bret's demos show incredibly innovative features, but at the same time, those features felt incredibly simple: easy to use, the feedback is obvious, and frankly, most of his particular examples don't seem that hard to implement. The hard part was coming up with the idea in the first place.
Plus, I can see 2 overarching principles in Bret's work: the first one is, using our visual system to see the relevant stuff at a glance. Give me a graph, not a listing. The second one is direct interaction. You could think of it as a REPL on steroids, or even a live image, but it's more than that. In a live environment, you would change a variable, and see the consequences in real time. Bret Victor goes beyond even time, and let us manipulate systems from the outside, as if they were a block universe (where time is just another dimension).
In learnable programming, you can see how he slides the force of the jump, to make it just right so our little Mario can go through that little secret passage. We can visualize the whole path (that's the first principle), and we can see what that path would have been if you change the laws of physics (that's the second principle).
Very deep stuff. Very hard stuff. But as I said, very simple as well. And I expect future insights will make it even simpler.
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Let us go back to my Earley Parsing for a second, because it's quite illustrative. My journey began with this talk[1] by Ian Piumarta. He mentioned Earley parsing at some point saying it was very general, handles every possible context-free grammars, and is also very simple, very easy to implement: half an hour to translate the algorithm in any language.
Months later, I'm still at it.
But you know what? As I come to understand Earley parsing, I agree with him more and more. This thing is genuinely simple. I wrote a recognizer in less than a hundred lines of Lua code, and the whole parser will likely take less than 200 lines. As I said, simple.
Simple does not mean easy however. Without the proper insights, I could only struggle. But then I stumble upon a sentence, a picture… and then something clicks. And I can see the simplicity, as well as the depth. And then it clicks again. And it becomes even simpler. To the point that now, I understand where Piumarta is coming from. And I still remember why it was so difficult for me back then.
I mean, Earley parsing did use to feel kinda complex, and quite ad-hoc. At the same time, it didn't seem too difficult. I was wrong. Earey parsing proved to be much more difficult, and at the same time much simpler, than I had expected.
