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Algorithms Interviews: Theory vs. Practice

danluu.com

41–50 of 77 posts

Re: Algorithms Interviews: Theory vs. Practice

#41

I actually suspect that one of the main purposes of the algo based interview process is a motivation check. It takes time to prep for these interviews. Lots of time. So if you get a candidate that is crushing problems, it can either mean two things: 1) They are exceedingly brilliant and they can program decently 2) They have studied hard, they can reason and code decently Combine that with a system design portion and…

I still see it as an age experience filter the further you are form college the harder and more prep time is required to bring up seldom used skills backup to proficiency.

Re: Algorithms Interviews: Theory vs. Practice

#42
post #31
post #22

Earlier quoted context omitted.

If we are one query from bring down the site I don't want to be anywhere near that site.

If you haven't had a single query bring down a service at least once, you just don't have enough industry experience with services. It's surprisingly easy to bring down complete complex services system with a unlucky degenerate case.

Ctrl+A, then Ctrl+C, followed by Ctrl+V, then Enter...

Re: Algorithms Interviews: Theory vs. Practice

#43

> When I ask people at trendy big tech companies why algorithms quizzes are mandatory, the most common answer I get is something like "we have so much scale, we can't afford to have someone accidentally write an O(n^2) algorithm and bring the site down". I think people who say this just don't get what's really going on here. If you look at these types of interviews, a big part of what they select for is: 1) Some sort…

I think most interviews are designed to find people similar to the interviewers, whether they realise it or not. If you think it works "well enough", I think you're just fooling yourself.

I say that as someone who has gotten a job offer from every interview I've been interviewed, and done maybe 100 on the interviewer side of the table. I put far more weight onto pair programming and anything that resembles a work sample than anything else. And even then you don't really find out what people are like until like the tenth pull request or so.

Re: Algorithms Interviews: Theory vs. Practice

#44

Earlier quoted context omitted.

I'm almost 50. I pass about two-thirds of all my on-site interviews, but have 100% failed my FNG interviews (I got an offer from Amazon 15 years ago but declined because I didn't want to move to Seattle). I've failed Google 4 times, Facebook 3 times, and Netflix twice. I think my biggest problem is because I'm so old, their expectations are even higher than what I realistically am. I'm okay being hired as a "senior s…

"Almost 50" means you're in your 40s. And you probably started interviewing in your mid-40s, at the latest, if you've already interviewed 4 times. The gist of your comment might be correct, but I think we shouldn't perpetuate the mindset that mid-40s or even 50s is "so old." In almost all knowledge-worker professions, age and experience is acknowledged as an asset. I think software companies are just starting to real…

I started interviewing at Google since about 2005 so over 15 years. I've seen the entire gamut of interview style questions, from trivia questions, to brain teasers, to easy algorithm questions, to the algorithm arms-race where LeetCode hard questions are now being asked. It has only gotten harder and the expectations as someone with 25+ years experience is too much. That is the biggest problem someone my age faces. I'm easily the best programmer on the team, but it's hard to show when I can't memorize 400+ LC questions for the FANG interviews.

Re: Algorithms Interviews: Theory vs. Practice

#45

>"I’ve done maybe 40-ish "real" software interviews and passed maybe one or two of them" I'd say that about mirrors my experience as well. Is this really that common? Here I was thinking that I'm just an idiot.

I'm almost 50. I pass about two-thirds of all my on-site interviews, but have 100% failed my FNG interviews (I got an offer from Amazon 15 years ago but declined because I didn't want to move to Seattle). I've failed Google 4 times, Facebook 3 times, and Netflix twice. I think my biggest problem is because I'm so old, their expectations are even higher than what I realistically am. I'm okay being hired as a "senior s…

> I'm okay being hired as a "senior software engineer" and working my way up, but they insist on interviewing me as a staff level, which I clearly am not capable of achieving.

> but it's those damn algorithm questions I just can't get past

I was under the impression there was a minimum bar on the algorithms that applies regardless of seniority and whether you pass the interview as a junior/senior/staff/etc. was mostly dependent on communication, system design interview, etc.

Re: Algorithms Interviews: Theory vs. Practice

#46

>"I’ve done maybe 40-ish "real" software interviews and passed maybe one or two of them" I'd say that about mirrors my experience as well. Is this really that common? Here I was thinking that I'm just an idiot.

I'm almost 50. I pass about two-thirds of all my on-site interviews, but have 100% failed my FNG interviews (I got an offer from Amazon 15 years ago but declined because I didn't want to move to Seattle). I've failed Google 4 times, Facebook 3 times, and Netflix twice. I think my biggest problem is because I'm so old, their expectations are even higher than what I realistically am. I'm okay being hired as a "senior s…

I'm curious how much you prepared for the interviews? I feel like after so many tries, you should have made it in (if just because you managed to get a set of questions you were familiar with). I think the reality is you need to dedicate serious time. I had one friend who got in pretty easily, he was a college dropout even, but he had been doing competitive coding for a couple years so pretty much knew every possible question.

Re: Algorithms Interviews: Theory vs. Practice

#47

> Some companies will give very large out of band bonuses to people, but that work wasn't for a company that does a lot of that kind of thing, so there's nothing the company could do to indicate that it valued additional work once someone did "enough" work to get the best possible rating on a performance review. From a mechanism design point of view, the company was basically asking employees to stop working once the…

> to try to get people to leave the team and join less effective teams From a director-level perspective it probably makes sense to have one or two of your best people on each team, rather than some wholly excellent teams and some wholly mediocre teams.

The IBM Black Team is a notable counterexample that argues clustering your top performers together pays extremely effective dividends.

Re: Algorithms Interviews: Theory vs. Practice

#48

>"I’ve done maybe 40-ish "real" software interviews and passed maybe one or two of them" I'd say that about mirrors my experience as well. Is this really that common? Here I was thinking that I'm just an idiot.

I’ve had 10 jobs over the past 30 years, and I’d say I probably interviewed at four places that rejected me for every one of the 10 that accepted me. My hit rate is a little higher than his, but not really that much - I think the main difference is the prestige of the places he’s interviewing.

Re: Algorithms Interviews: Theory vs. Practice

#49

I actually suspect that one of the main purposes of the algo based interview process is a motivation check. It takes time to prep for these interviews. Lots of time. So if you get a candidate that is crushing problems, it can either mean two things: 1) They are exceedingly brilliant and they can program decently 2) They have studied hard, they can reason and code decently Combine that with a system design portion and…

Same reason they mostly require college degrees even though most of the work we do isn’t anything we learned in college - it’s a check to see if you’re motivated enough to stick with something difficult.

Re: Algorithms Interviews: Theory vs. Practice

#50
post #43

> When I ask people at trendy big tech companies why algorithms quizzes are mandatory, the most common answer I get is something like "we have so much scale, we can't afford to have someone accidentally write an O(n^2) algorithm and bring the site down". I think people who say this just don't get what's really going on here. If you look at these types of interviews, a big part of what they select for is: 1) Some sort…

I think most interviews are designed to find people similar to the interviewers, whether they realise it or not. If you think it works "well enough", I think you're just fooling yourself. I say that as someone who has gotten a job offer from every interview I've been interviewed, and done maybe 100 on the interviewer side of the table. I put far more weight onto pair programming and anything that resembles a work sam…

Getting an offer from every interview is impressive, good for you (you don't cite how many but I'm assuming you've done a good number in different contexts). Even the smartest people I've known have had mixed luck with interviews, due to some combination of randomness, poor interview design, or just poor fit for that company. As for administrating 100 interviews, you'd prob rack those up in a 2 year stint at a FAANG (usually they'd start you around 6 months in or earlier and you'd do 1-2 per week thereafter).

Anyway, yes, interviews are prone to bias. So are work samples (in different ways). Pair programming can be better but logistically harder (i don't know any companies that have been able to do them at FAANG scale), but even then, like you said, you'd need a lot of it to really judge.

At the end of the day, the entire hiring process needs to work "well enough" and with reasonable cost to both company and candidates. For many FAANGs, these interviews (plus hiring committees, bar raisers, or something else) meet that criteria... Though honestly, they often fall short on diversity but that's a whole other topic.

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