[TimMurnaghan]

If you're using a small subset why on earth is it the right language? I had the misfortune to try to mentor a new quant who felt they had to write C++ "for speed" . But refused to use the STL as they were going to use a subset. So they wrote Fortran-like C++, array as the only data structure, bad lookup algorithms and leaked like a sieve.

Things are in the language for a reason - if you've got the issue then you use the feature.

I hardly ever recommend C++ these days as it's not worth the slower dev time. There are a few cases where run-time really does trump everything else and it's still appropriate.

In that case the code will be templated to within an inch of its life, because that's how to write real C++.

[dig1]

Because with small subset you get pretty and understandable code with reasonably fast build time.

Although STL implementations are getting closer today (regarding underlying speed), unless you plan to lock to particular implementation, even version, you'd better use subset ;)

[bitcoinmoney]

Are you a quant? What do you use instead of C++? Python/cython? I’m not convinced C++11/17/20 cannot be used in quant but I am not in the business (i’d Love to though).

[bsenftner]

Let's just be honest: today's dev's can't write in C/C++ because they don't have the formal training. They are primarily script language devs who can't work at the low level required by C/C++. The formally educated programmers who were taught low level large-scale systems programming are too few to create the programmer farms you all work it (which I left for scientific software development, where the devs are older and we all work in C/C++ or assembly.)

[ahartmetz]

You don't need formal education to understand why some things are the way they are in C++, you need to understand how a CPU works. A small amount of assembly programming is sufficient for that - it is actually very simple to understand, just hard to write nontrivial programs...

[atomic-hedge]

I'm very interested in leaving the dev farms for something more interesting. I'm taking steps in that direction, but do you have any advice on how you escaped into scientific software dev?

[dig1]

Not OP, but worked in science before. What you want is not to work in science on software dev ;) Scientists usually write extremely ugly, messy code, just to make it working and finalize paper for publishing. Remember, their focus is paper not code nor properly workable program.

Things like testing, agile, tickets, code indentation, patterns - none of that you'll find there.

If you aim for serious environments like Wolfram Research or MathWorks, that could be different. If you aim for quantitative firms, usually you'll find there scientists writing prototype in mathematica/matlab/r/python (messy again) and devs who will re-write it in c/c++/java/asm.

[atomic-hedge]

Thanks for the suggestions! I hadn't thought about places like Wolfram Research or MathWorks. I'll keep my eye on those. I'm working on picking up more C++ since that seems to be what everything I'm interested in is using.

[bsenftner]

Keep in mind these are "conservative developers" - they work in C/C++ - meaning a preference towards C styled C++, a preference towards maintainability, and a preference away from the latest features of C++. That is being a developer, yet in a tech shop. There are lucrative alternatives too:

When one looks outside the traditional technology industries, there are a huge number of technology jobs as the tech person in a non-tech industry, being forced into the tech world. These tend to be C-Suite level jobs, so picking up an e-MBA is also be pretty good idea - to know how to talk and operate in their terms, how and why what you're doing for them is what you're paid to do. They have no idea, and very likely a history of being burned by low level tech consultants.

[atomic-hedge]

Thanks for the info. I'm kind of burned out on the shiny new things, so C and maintainability sound like a breath of fresh air. I think reading an OS paper from ~1983 that described what is effectively Kubernetes (with working prototype written in ML) really drove home how little the fundamentals of our industry change.

The way I describe my career goals now is: I want to work in a domain where quality and performance is the product.

I hadn't considered getting an MBA and using it in that way, that's something that I will take a hard look at. Thanks for the advice!