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).
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.
