Stanford's Encyclopedia of Philosophy is a peer-reviewed, academia level resource. Basically a classroom accepted Philosophy Wikipedia. I wonder if there are similar academic resources for other subjects?
Detailed articles on Turing and the Turing Machine.
Something I'm not grokking:
In the exposition the list of examples presented as typical of Computer Science – "certainly not just programming" – is this one at the end of the list:
"... the design of embedded systems ..."
Huh?
Why doesn't that fit? There is no further direct discussion on the page that could apply (that I found). Is it a modern perspective that the embedded world and the high-end world are becoming so blurred as to be identical (such as Linux on both)? Is it simply Moore's law in action reducing the cost of embedded solutions to the point that embedded design is no longer something special?
The other examples, "the construction and optimisation of compilers, interpreters, theorem provers and type inference systems," clearly hit meta-activity more than "just programming."
Maybe it means embedded design is a transcendent synthesis? http://catb.org/jargon/html/story-of-mel.html
The joy of (hardware related) spinlocks and related contention control algos that non-embedded systems would resolve with the reset button and/or blaming the operator.
Mergers of a lot of classical engineering control theory and computer science (although not limited solely to embedded).
I don't think anyone in industry writes mathematically provably correct software except embedded aerospace.
As much as it pains me to say it, on a multidecade basis, exception handling and testing seems to be retreating to life-critical embedded work, even if in the rest of the biz those topics get a lot of PR.
I think they're writing about "real" embedded like the space shuttle autopilot as opposed to "its just a PC w/ PC app, but not typical PC hardware and outside a cubicle" like an asterisk appliance or a linux based small NAS appliance.
At the moment the majority of the articles are on computational neuroscience, but it is slowly starting to expand.