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by dkersten 2707 days ago
No, but its a really easy algorithm, it really shouldn’t be too hard to implement given a description of it.

(not accounting for the people who are just bad at writing anything on the spot in a high pressure interview situation, of course)
1 comments
tptacek 2707 days ago
It doesn't matter if it's a really easy algorithm if it's trivia or unrelated to the job.
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drenvuk 2707 days ago
How do you know that implementing a feature very close to how BFS works won't be necessary in the job? You can't. At this point asking if a candidate can make BFS is akin to asking if they can count. Same thing for inverting a binary tree or doing fizzbuzz. They're general and easy enough that anyone with a programming background should be able to figure them out.
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akerl_ 2706 days ago
Given that the hiring process has time constraints (however you do hiring, you can’t use infinite time, so you need to pick what you’ll include in the process), why use time testing the candidate’s ability of something that might be necessary in the job. Wouldn’t that time be better served testing something you know will be necessary?
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drenvuk 2706 days ago
You ask about things you know will be necessary as well. In an interview the time shouldn't be spent entirely on academic programming questions. They're there only to gauge problem solving skills in real time in a stressful environment, which work sometimes is. Who says you can't fit any of the above mentioned programming problems in 10 to 15 minutes?
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akerl_ 2706 days ago
Wouldn’t asking real-world questions that the person will definitely run into during the job also gauge problem solving skills? Unless problem-solving isn’t part of the real job, in which case it’s not worth testing for.

If your point is that you do a mix of questions that are definitely relevant and some that are academic and might be relevant, why not just do 100% known-relevant questions? What’s the value add of asking questions that are less than 100% relevant?

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tptacek 2706 days ago
Here's a simple way to quantify the argument: go find the most popular Node or React front-end projects on Github, and then find out how many of them --- in their own source code, not in the vast, unending dependency tree NPM generates --- contain a breadth-first search.

My guess is: not very many.

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