One Problem is, that we first have to clearly define the construct that we want to measure with the test. That is not often clear and often underdefined. When designing a test, we also need to be clear about what external influences contribute to noise / error and which are created by the actual measurement. There never is a test that does not have a margin of error.
A simple / simplified example: When we measure IQ, we want to determine cognitive processing speed. So we need to have fixed time for the test. But people also may read the questions faster or slower. This is just a typical range, so when you look at actual IQ tests, they will not give a score (just the most likely score) but also a margin of error, and test theorists will be very unhappy if you don't take this margin of error seriously. Now take someone who is legally blind. That person will be far out of the margin of error of others. The margins of errors account for typical inter-personal and intra-personal (bad day, girlfriend broke up) etc occurrences. But this doesn't work here. So we try to fix this, and account for the new source of error differently, e.g. by giving more time.
So it highly depends on what you want to measure. If you are doing a test in CS, do you want to measure how well the student understood the material and how fast they can apply it? Or do you want to measure how fast the student could do an actual real-live coding task? Depending on what your answer is, you need a very different measurement strategy and you need to handle sources of error differently.
When looking at grades people usually account for these margins of errors intuitively. We don't just rely on grades when hiring, but also conduct interviews etc so we can get a clearer picture.