The whole psychology around tech interviews tends not to be focused on the right things. At least in the general sense, a lot of it appears to be people copying others without understanding the motivations.
The theory of interviewing should be to ask questions that are as predictive as possible e.g. success on the interview correlates as closely as possible with success on the job. The strengths needed will vary greatly by the role, company, and so on.
But what you tend to see is, everybody has a handful of "pet" questions that they ask over and over, without applying strict rationale for why its predictive to success.
Personally, any good interview question must both be iterative and highly correlated with actual work. Questions that have one "trick" and judging on that basis is a poor interview. Questions that focus on data structures or algorithms that aren't going to be relatively common are also poor. Questions which lack real world applications, also poor.
At least for me, I have a handful of questions, but one of my basic ones is to implement a certain data structure. And honestly, I care more about seeing the naive solution than the highly optimized one... because I care first and foremost that the candidate can code proficiently. The naive solution is super easy and requires little theoretical strength... but it becomes very obvious how proficient of a coder they are by seeing them write out the solution. How quickly can they write it? Do they make syntax errors? How long to grasp the intention of the question?
Some write the solution in 5 minutes, some take 40 minutes. That gap alone is probably the most strong predictor.
There is a more theoretically optimal solution, but I just followup at the end and we'll talk through what it could be. But if somebody can hammer out a naive solution with good code quality, quickly I weight that about 90%.
But my company also needs strong coders over particularly theoretical people. One of my best coworkers bombed on a tree interview questions I asked... but I could tell from all the supplemental details that he was very strong.
The theory of interviewing should be to ask questions that are as predictive as possible e.g. success on the interview correlates as closely as possible with success on the job. The strengths needed will vary greatly by the role, company, and so on.
But what you tend to see is, everybody has a handful of "pet" questions that they ask over and over, without applying strict rationale for why its predictive to success.
Personally, any good interview question must both be iterative and highly correlated with actual work. Questions that have one "trick" and judging on that basis is a poor interview. Questions that focus on data structures or algorithms that aren't going to be relatively common are also poor. Questions which lack real world applications, also poor.
At least for me, I have a handful of questions, but one of my basic ones is to implement a certain data structure. And honestly, I care more about seeing the naive solution than the highly optimized one... because I care first and foremost that the candidate can code proficiently. The naive solution is super easy and requires little theoretical strength... but it becomes very obvious how proficient of a coder they are by seeing them write out the solution. How quickly can they write it? Do they make syntax errors? How long to grasp the intention of the question?
Some write the solution in 5 minutes, some take 40 minutes. That gap alone is probably the most strong predictor.
There is a more theoretically optimal solution, but I just followup at the end and we'll talk through what it could be. But if somebody can hammer out a naive solution with good code quality, quickly I weight that about 90%.
But my company also needs strong coders over particularly theoretical people. One of my best coworkers bombed on a tree interview questions I asked... but I could tell from all the supplemental details that he was very strong.