Befunge VS Oberon

1. C compilers don't do a good job, & thus even CPython, which has historically stuck to rather vanilla C, uses computed goto, as described in https://eli.thegreenplace.net/2012/07/12/computed-goto-for-e...

I resorted to similar techniques in optimizing Befunge: https://github.com/serprex/Befunge (See bejit.c & marsh.c/marsh.h)

2. Rust enums are not variable sized, think of them as tagged C unions, where the Rust compiler can sometimes apply tricks to make Option> the same size as Vec

3. match can specialize for straight forward cases, when in doubt use https://godbolt.org

I've found async to be straight forward anytime I've used it. Promise#then is equivalent to callbacks

async/await often requires very little changes compared to synchronous code, whereas reworking a program into callbacks is much more impactful. & the async/await compilation process tends to produce better performance in addition to this. My first async/await work was a few years ago to increase a data importer's performance by an order of magnitude compared to the blocking code

Here's an example where looping made for a callback that recursively called, using async/await I get to use a plain loop:

before: https://github.com/serprex/Befunge/blob/946ea0024c4d87a1b75d...

after: https://github.com/serprex/Befunge/blob/9677ddddb7a26b7a17dd...

I don't see why people find it so complicated to separate begin-compute & wait-on-compute

I've since rewritten a nodejs game server into rust, https://github.com/serprex/openEtG/tree/master/src/rs/server... handleget/handlews are quite straight forward

You'll also find them used in CPython's ceval.c

I use them in both my C befunge implementations:

https://github.com/serprex/Befunge/blob/c97c8e63a4eb262f3a60...

https://github.com/serprex/Befunge/blob/c97c8e63a4eb262f3a60...

> Sure there's a small overhead to smart pointers

Not so small, and it has the potential to significantly speed down an application when not used wisely. Here are e.g. some measurements where the programmer used C++11 and did everything with smart pointers: https://github.com/smarr/are-we-fast-yet/issues/80#issuecomm.... There was a speed down between factor 2 and 10 compared with the C++98 implementation. Also remember that smart pointers create memory leaks when used with circular references, and there is an additional memory allocation involved with each smart pointer.

> Garbage collection has an overhead too of course

The Boehm GC is surprisingly efficient. See e.g. these measurements: https://github.com/rochus-keller/Oberon/blob/master/testcase.... The same benchmark suite as above is compared with different versions of Mono (using the generational GC) and the C code (using Boehm GC) generated with my Oberon compiler. The latter only is 20% slower than the native C++98 version, and still twice as fast as Mono 5.

Great, thanks!

There are books online for free, e.g.

https://people.inf.ethz.ch/wirth/ProgInOberonWR.pdf

and https://ssw.jku.at/Research/Books/Oberon2.pdf

Oberon+ is a superset of Oberon 90 and Oberon-2. Here is more information: https://oberon-lang.github.io/, and here is the current language specification: https://github.com/oberon-lang/specification/blob/master/The.... I already had valuable feedback here on HN concerning the channel extensions. Further research brought me to the conclusion, that Oberon+ should support both, channels and also monitors, because even in Go, the sync package primitives are used twice as much as channels. Mutexes and condition variables can be emulated with channels (I tried my luck here: https://www.quora.com/How-can-we-emulate-mutexes-and-conditi...), but for efficiency reasons I think monitors should be directly supported in the language as well, even if it might collide with the goal of simplicity.

Feel free to comment here or e.g. in https://github.com/rochus-keller/Oberon/discussions/45.

> Does anyone know why Wirth never modernized his style?

Readability. It's easier to read the source code with uppercase keywords. (I think Wirth once said that code is written once but read many times). See this source code - https://raw.githubusercontent.com/rochus-keller/OberonSystem... - to get an idea of this (the uppercase keywords allow you to easily scan the blocks of code). Ofcourse, one can claim that the same can be achieved better today with colour-coded keywords.

If I remember right, the Oberon+ IDE - https://github.com/rochus-keller/Oberon - gives you an option to disable this and use lowercase keywords.

> gain a deep understanding of it .. generate smaller subsets of the system

You can use the OberonViewer for this purpose with the original source code, or the Oberon IDE with a version of the Project Oberon System which runs with SDL on all platforms, see https://github.com/rochus-keller/oberon/#binary-versions and https://github.com/rochus-keller/OberonSystem/tree/FFI

> Regardless, which one is more likely to be ported to a different architecture in the future?

Not sure I understand the question. I'm talking about CPU architectures. The current implementation is in x86 assembler. So if you want to run it on AMD64 or ARM, then you have to replace all assembler files, in the present case probable the full source code.

> what are the comparative performance benchmarks of the low-level language versus the high-level language?

I don't have any measurements. But consider that many operating systems are implemented in C (e.g. Linux) with only isolated parts in assembler, so it is easier to port to other architectures. Linux apparently is fast enough and available for nearly every CPU. Oberon in contrast to C is garbage collected, which also affects performance. I have measurements comparing the same benchmark suite implemented in C++ and in Oberon, where the former is about 22% faster (see https://github.com/rochus-keller/Oberon/blob/master/testcase...).

I actually had a similar problem some years ago and finally moved away from LLVM because of complexity, continuous research effort and performance. My current Oberon+ implementation works like this: the CIL code generator together with Mono is used during development, integrated with the IDE, using the debugging features integrated in Mono; to deploy the application and to gain another factor 2 of performance C99 instead of CIL can be generated and compiled with any compatible toolchain. Here are some performance measurements: https://github.com/rochus-keller/Oberon/blob/master/testcases/Are-we-fast-yet/Are-we-fast-yet_results_linux.pdf. Compiling to CIL is very fast and the time Mono needs to compile and run is barely noticable.

> annoying aspects was requiring the .NET runtime ... OpenJDK is a blessed implementation in a way that Mono never was

Which is unjustified, because Mono CLR is just a single executable less than 5 MB which you can download and run without a complicated installation process (see e.g. https://github.com/rochus-keller/Oberon/#binary-versions ). AOT compilation on the other hand is a huge and complex installation depending on a lot of stuff including LLVM, and the resulting executables are not really smaller than the CLR + mscorlib + app.