[thezilch]

Holding in my brain and using all these "modern" features increases the time I need to think about code, data, and algorithms, and that's usually where most coding spends my time -- thinking.

And "modern" compile times... increasing the time between results and further thinking and writing. Don't forget that; the article doesn't.

And "modern" debugging... well, good luck.

[Koshkin]

Well, people have been known to hold in their brains information pertinent to their trade. Professional training helps, too. I can only guess the extent of what a mathematician, a physicist or a medical doctor must remember to be successful in what they do.

[pjmlp]

Musicians are able to hold complete compositions on their heads, some of them several minutes long.

It is all a matter of focus and pratice.

[kgabis]

Code is not music. When thinking about code you must keep track of possible branches executed code might take and properties of the physical machine it runs on. C++'s complexity can hide code's underlying logic and make some types of bugs more common.

[pjmlp]

As someone that learned music and several instruments before getting into computing, and having spent several evenings with musician friends, I beg to differ.

Writing a composition score for an orchestra falls under similar conditions, how each instrument sounds, how they sound together, when each comes and goes into play, and so forth.

Most complaints about C++'s complexity can be equally applied to languages that look deceivably simple like Python.

Complexity is like thermodynamics, it gets pushed somewhere, if it isn't on the code, it gets shoved either into boilerplate, or architecture.

[thezilch]

If we can compare C++'s complexity to Python's, then C++ has lost its way. You're saying the same thing as the article and my comment, that C++ is trying to hide complexities, and we're arguing that doing so is instead adding more complexities.

Sure, Python makes it easy to listen on a socket, parse HTTP, and send HTML down -- hiding a lot of complexity. But it's made it impossible to do so very efficiently and scale up. Try and dive into Python's stack for that (Re: 'hold in your brain all the "modern" features'), and you'll get lost in a myriad of CPython (or whatever flavor you choose) generics and indirection that you can't optimize. Startup times matter, because you are all about hiding complexities and went "serverless" and constantly eat cold starts (Re: '"modern" compile times').

I think it's apt to compare "modern" C++ as moving towards something like Python. Not great for a lot of applications of C++ (Re: games, in the article and my focus) or its perceived goals as a better C. That's the point. Many of the C++ additions are being slagged for making a worse C. It's looking nothing like C any longer. It's a giant ball of complexity with dozens of ways of doing the same thing and hoping you learned them all.

This is why I think languages like Rust (or even Go) get a lot of attention. They have a good interop story with C, like C++ has. And if we're going to learn a bunch of non-C looking language grammar, C++ is doing a worse job.

[pjmlp]

My point about Python is that it is always presented as begginer friendly language, yet is it quite complex for anyone that whats to fully master it.

The language + standard library + C API references are around 2392 pages, not counting the other minor documentation like the 500 PEPs, release notes and differences across each Python release, even minor ones.

Then there is the whole set of meta-classes, decorators, mixins, generators, operator overloading, multiple inheritance, abstract classes, fp like programming and much more.

The big difference to C++, is that the community doesn't care about performance, leaving the PyPy guys a Quixotic battle regarding adoption, which isn't the case with C++ compilers.

Even C isn't as simple as many think, with its 200+ documentated cases of UB, and the days that C mapped 1:1 to PDP 11 Assembly are long gone.

How C code looks like, and what gets generated via auto-vectorization, GPGPU code, SIMD intrisics are very much two worlds appart.

[thezilch]

You're absolutely right that Python has also become more and more complex and often not for the best.

As for Python performance, on the contrary, I think there was a large portion of the Python community that did care during my years with it. I think 3.x adoption was hurt a lot by being slower than 2.7.x. I think a lot of the community jumped ship to Golang or similar, for both performance and complexity reasons.

I would absolutely love for C++ to tackle C UB or make incompatible insecure C. Instead, we get stuff like Ranges, time and again. I'm struggling to understand what complexities you are finding it covers that are worth supporting forever, committing gray matter, committing productivity loss, committing debug travesties, &c. Say I'm a musician that can hold complete compositions in my head; why should I commit this feature and its baggage to memory?

[kgabis]

As someone who also learned music and played several instruments (violin, piano) before getting into computing I still don't get what's the point of comparing musical memory to being able to recall programming language rules. Programming is largely about managing complexity and our mammal brains are not very good at keeping track of all the exceptions and special cases a language like C++ is full of (as opposed to remembering music). Just to be clear: Yes, writing music, especially for an orchestra, IS hard and complex.