[brian_spiering]

The issues you describe are important but typically out of scope for data structures and algorithms book. They are often considered more architectural issues.

In many real-world scenarios, it is not necessary to pick the best data structures and algorithms. It is often good enough to just avoid poor choices.

Trustworthy measurements are important since constants and implementations matter. That is done through benchmarking and profiling. This is also often not considered part of many data structures and algorithms books.