I'll have to disagree. It's not a matter of personal preference. Those tools scale only into a few hundred blocks, and even for naturally visual things (like logic circuits designing) people can only grasp more complex constructions when they are text. Even if you make the same abstracction blocks available in both.
Those architects probably just don't hit their limit. Physicists are all the time reaching their limit on LabViz scripts, and very vocal about it.
I have built many large applications in LabVIEW (>1,000 VIs), and I can easily state there is no inherent fault in being to build large systems with a graphical language vs a text-based one. Why? Because I have actually done it, resulting in extensible and maintainable code. The dataflow nature of the language makes it easy to understand how data flows through your system. It even has by-value OOP and an actor framework.
Physicists complaining about it have no merit because they have zero idea about software development, architectures, design patterns, etc. They love Python for whatever reason and don't complain about it, yet it's still terrible code. I have seen LabVIEW sworn off by top of the line physicists only to be shown their Python program that was a single file with about 15,000 lines of code and such atrocities as functions with greater than 20 arguments spread over 10 lines. It was an atrocity.
I have written multithreaded applications in Python, and the equivalent LabVIEW application would be far simpler because you get multithreaded behavior for free.
Many software engineers swear graphical languages are only for toy applications, but yet they've never actually built anything of note themselves in one. So it's a poor argument to listen to (as in the person you replied to) when it's purely speculation based on no real data. They somehow forget that they spent four years in college getting it drilled into their head that linear, text-based files are the only way to program a computer. It's interesting to note than any high level thought (e.g. mathematics) bears more resemblance to graphical notation than pure text-based notation.
Exactly! The more general the structures you're thinking about, the more visual approaches seem to become effective. That's my experience and Hadamard has some good discussion and data on it being a widespread trend in mathematical thinking.
Maybe a good approach for thinking about (at least partially) visual languages is considering which approaches are effective in thought for which types of subject matter. It definitely seems like the more general/abstract/high-level thought-categories make better use of relationship-focused visuals.
Also: that's why 'LabViz' yielded no seemingly relevant results on image search...