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Comment by tjr | Hacker News Reader

Wikipedia describes "computer science" as an umbrella term covering everything pertaining to software development and algorithmic thought. Academic computer science programs generally offer courses in both the theoretical and the applied.

Even the very term itself has often been described as a misnomer, not necessarily having anything to do with "computers" or with "science".

I think the reason people mix such things around so much is because what "computer science" is has been ambiguously defined all along.

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The truth is, CS is not a "science" like biology or physics.

It is an education in understanding computation and software development.

I'd also argue it is not an engineering discipline either. It's unfortunate the terms "Computer Science" and "Software Engineering" were ever accepted. They're holding us back; we're stuck in an outdated view of the subject.

I kindof disagree. For example while studying UML, it became more and more apparent to me how legitimate it is to have the word "science" in "Computer Science". Being able to create a high-level framework that is general enough to apply pervasively to IT systems is not a trivial matter, and requires considerable academic effort and creativity. The domain may be different from biology or physics, but the methods of obtaining that"understanding" you mention are strikingly similar (which accounts for the reliability of the results that are delivered).

Wait, did you just bring up UML as an example for backing up the claim that CS is science?!

I know UML is not very popular, but as you can see, I thought it was interesting.

In science, understanding is developed through abstract mathematics and empirical experimentation.

Whilst UML is an abstraction language, I would hesitate to compare it to a mathematical calculus. Regardless, we do not subsequently carry out empirical experimentation in the same way as science does. There is no "ground truth" that UML is modelling when developing software (ignoring edge cases) - it's a design tool.

They had to study existing software (empirical), and then find an understanding of what is essential and common to all cases.

The result was that a finite and compact set of concepts could be used to account completely for almost any design architecture, past or future. To me, this is pretty scientific.

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