[vonmoltke]

As an electrical engineer who briefly flirted with computer engineering, I had 4 semesters of continuous math and 1 semester of discrete math[1]. I also had classes like linear systems and electromagnetics where I had to actually use continuous math heavily.

While I do not think continuous math is particularly useful for general software development, I think it is very valuable for specific problem domains. I have found my Calculus/DiffEq foundation to be very valuable for my work with radar signal processing and NLP code, more so in the former because it was basically translating electrical engineering algorithms, formulas, and concepts into C. It is also important for any type of development that makes heavy use of geometry.

As a side note, I saw some of the bias you describe out of the more "pure" EEs I worked with when I first started. There was a strong bias against software engineers, particularly those who went the CS route, because they didn't understand the math and physics behind the hardware. Admittedly, some were clueless and probably should not have been writing software for multi-million dollar hardware[2]. Most were competent, though, and able to pick up the basics they needed to know when tutored for a bit.

[1] Which was actually titled "Discrete Mathematics", and was just covered basic set theory, combinatorics, and linear algebra. [2] Like the one who added a reset routine that blindly opened power contacts on the UUT without verifying that the power supplies were off first. Fortunately, that was caught before they actually opened with hundreds of amps going through the bus.

[mcguire]

As you say, continuous math (to my mind, calculus, diffeq, and linear algebra; anything involving reals) is necessary for some problem domains. But accounting is necessary for some problem domains as well. And molecular biology.[1]

But if I get worked up into a good froth, I can make a case that software development is applied formal logic or applied abstract algebra (or both). I don't believe you can do professional software development (in Weinberg's sense) without some serious discrete math, in the same way you can't do signal processing without calculus.

[1] If you've got something that mixes the three, let me know. It's probably something I should stay away from.

[vonmoltke]

I must admit to ignorance of Weinberg's books and other writings. My interest is piqued now, though.

That said, based on your second statement nearly all scientific and engineering programming would not qualify as "professional software development". The code I worked on had little to no discrete math or formal logic in it. There was not an integer to be found save loop counters and array indices Do you not consider an (electrical engineer | mechanical engineer | physicist | molecular biologist) who can code and spends the vast majority of their time writing production code like this a professional software developer?