If you're lucky, the system you're trying to simulate has good in-vivo recordings. That way you can compare the in-silco models directly to the real ones using either firing rates, LFPs, or other neuronal dynamic. Unfortunately, most of the time that isn't the case.
Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.
The first thing you said is correct. To do a proper simulation you would need to gather functional properties of the various cell classes and their synaptic connection, which this study didn't do. (Maybe you can find that information from other lab, I'm not familiar with fly models?)
However we definitely have the computational ability to do simulations a fly network. Look at some of the modeling done by the Blue Brain Project or Allen Institute for Brain Science - they do simulations of rat and mice models with hundreds-of-thousands to millions of neurons and exponentially more synapses. 3000 neurons is not that many. If you stuck to non-compartmental point models a 3,000 neuron simulation could probably be ran on a moderately high-end laptop.
But as said before, the physical connectome is only part of the information you'd need do any worthwhile simulations.
Having an understanding of mathematical foundations and proofs can be very beneficial to software developers; but I agree there are much better books than the ones suggested here. "Elements" is an historically important book (arguably the most important in math), but like you said is fairly outdated. Real Analysis is critical for higher level maths and theoretical computer science and does have some value even in software development. But with books like Spivak's Calculus you spend more time memorizing definitions and theorems than abstract thinking or problem solving.
Some better math books that I would recommend off the top-of-my-head:
* "How to Solve it" by George Polya - A great book on breaking down complex problems.
* "Mathematical Logic" by Stephen Kleene - A much more contemporary math book on building axiomatic theories from scratch.
* "Godel, Escher, Bach" by Douglas Hofstadter - Also about mathematical foundations but for a much broader audience.
Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.