To be honest, as a part of hiring procedure, it has its merits. In an ideal world, you want to ask the candidates a problem that is well defined, and applies th

To be honest, as a part of hiring procedure, it has its merits. In an ideal world, you want to ask the candidates a problem that is well defined, and applies the tools that they might have learned in their past. This is why algorithmic problems are common - a large pool of candidates have recently finished school, they have a lot of fundamental knowledge from their experience there (and nothing else), and asking these is a way to evaluate [ how well is this problem approached ] with [ tools they should have at their disposal]. It's more about can you understand what you have learnt and use it to solve a novel thing, and less about can you balance a binary tree given 100 integer inputs. It's largely devolved in a cat and mouse game now, with candidates spending a large part of their time poring over CLRS or on Leetcode, and companies asking increasingly difficult (and serving no purpose but testing how much time was spent on practising) whiteboard questions.