11 ms·

The only reason it seems to even learn them is to pass an interview... What a utterly stupid and broken process. All it's testing is recall, that you've memori

by LandR 8y ago

The only reason it seems to even learn them is to pass an interview... What a utterly stupid and broken process. All it's testing is recall, that you've memorized some algorithms that 99% of developers will never need. Especially when these are really hard problems that people have studied for years, to think that anyone who hasn't memorised the solution is working this stuff out in an hour on a whiteboard is craziness.

franzwong 8y ago
I would say it depends. I have been working in this industry for 12 years but I don't need to use those knowledge. However, if you read source code of popular frameworks and systems, they use a lot of those algorithms and data structures.
TomMarius 8y ago
I'd learn it just for the knowledge, I have no desire to go into the interviewing process again. I agree that interviewing is a broken process.
BJanecke 8y ago
There is nothing about learning how basic data structures and algorithms work that won't help you in your day to day development. You might be "fine" without it in a certain category of job, but rather than be dismissive about it you could be excited about having a massive wealth of information that you can use to do your job better. There will always be something else to learn, wether it be how to apply Domain Driven Design to your work or how to work with graphs when munging data. It's always worth it. [edit] Run on sentence
- octorian 8y ago
  > There is nothing about learning how basic data structures and algorithms work that won't help you in your day to day development. Having a basic understanding of these things is NOT the same as being able to regurgitate them on a whiteboard, under the stress of the interview process.
  - LandR 8y ago
    Exactly, I don't need to know this stuff of the top of my head. I can look it up...
    - lordCarbonFiber 8y ago
      The reason we test for things is to verify you have enough domain knowledge to "look it up". A bad interviewer will ask you to write quick sort on the board, because if we've already gotten to the point of "implement quick sort" yeah we can just look that up. However, if you're given a collection of nodes and asked to do something with them; that's a bit more interesting. If you know nothing about graph traversal, or have never seen a tree (both not uncommon in people claiming to be principle engineers in my industry) how do you even know what to search for? Best case is you're smart and waste time coming up with a new solution from first principles; most likely it just never gets done.
gumby 8y ago
> The only reason it seems to even learn them is to pass an interview... While I agree that the process is broken, a solid understanding of algorithms and data structures is very important for developers at my company. And nobody knows all, or even most of the algos or data structures! But we do have large amounts of data and some pretty complex analytic problems, and a poor design can cost a lot of time and AWS $. Likewise over-engineering something small is a waste of time not just in writing but maintaining it. I agree that most e-commerce or business web developent probably don't need this level of formal skill. Whiteboard questions are useful, but not for figuring out trick questions. Instead for figuring out how the candidate approaches problems.
- kamaal 8y ago
  Those look like software design skills. Also the type of systems you describes use something like Hadoop, and use things like Hive and Pig on top of it. Once you get the data out you use Python or R. And you generally use a standard library to work with. That really SQL + general programming. What new problems are you working on that require you to invent novel algorithmic techniques?
  - C4stor 8y ago
    Even after choosing a technology (like Hadoop), there's a lot of difference between the best and the worst algorithm to solve a problem. For example, the reduce phase of MapReduce is pretty much "apply the algorithm you want on this List", and that's where knowing good list algorithms (for example) shine.
    - kamaal 8y ago
      Sorry, in almost all cases its really choosing over several ways of Joining the data, not writing SELECT *, not writing cross joins and learning SQL well. Which why I ask again. Please list your problem which is so novel it requires you to invent a novel algorithm. Please note statistics is a science that has existed for centuries now. Unless you are in a university, its highly unlikely you have a problem that will need to you to work on something that novel.
intkj 8y ago
What better way is there to try and get the best assessment of someone’s coding ability in a 45 minute timeframe?
- TomMarius 8y ago
  IMO not doing it. Why'd you do it? There are much more important factors than someone's ability to do a whiteboard exercise while under stress. You can e.g. check their Github, ask them to make a simple example project at home, etc.
  - sgc 8y ago
    This. Test them using the tools they will be using every day.
- LandR 8y ago
  You aren't testing their coding ability though you are testing their ability to remember how to implement a very specific algorithm.
fsloth 8y ago
"these are really hard problems that people have studied for years" Because of this. So that when you encounter a problem, you know how it can be solved efficiently. If you disregard existing knowledge, you are likely to spend a lot of time cooking up something complex and half-assed that creates an unnecessary maintenance load. Like music is composed of fundamentals, similarly most problems in computing can be decomposed such that familiar approaches can be applied to them. I think the categorization of Aho's "Foundations of Computer Science" is pretty much to the point on which fundamental formulations are practical to know.
- kamaal 8y ago
  >>If you disregard existing knowledge, you are likely to spend a lot of time cooking up something complex and half-assed that creates an unnecessary maintenance load. Unless you are stuck on an Island coding during a vacation, not one person on earth faces this kind of a situation. Almost anybody doing anything apart from basic beginner level coding work knows to look up to a solution on the internet if a solution is not scaling already.
  - fsloth 8y ago
    "Almost anybody doing anything apart from basic beginner level coding work knows to look up to a solution on the internet if a solution is not scaling already" This applies to some practical areas, but some are murky and need more than agile google-fu to waid through of an algorithmic jungle to a solution that provides added value to end user. There is a discipline and domain dependent threshold where the internet suddenly becomes obscure and unhelpful when one is trying to find solutions. In these instances either you are solving the wrong problem, or the problem is quite complex and/or does not have a closed form/ready solution. The best thing to happen in these instances is that one can limit ones input domain just so that it maps to some algorithmic concept or another. It's not rocket science, but in these instances having an intuitive feel toward the big O behaviour and various algorithmic constructs is really, really helpfull. Sometimes you just need to implement your own fudged QR decomposition and understand a little bit of numerics, or build custom octrees and whatnot. Couldn't really do it without my books. I do CAD and computational geometry stuff, YMMV.

by LandR 8y ago

franzwong 8y ago

I would say it depends. I have been working in this industry for 12 years but I don't need to use those knowledge. However, if you read source code of popular frameworks and systems, they use a lot of those algorithms and data structures.

TomMarius 8y ago

I'd learn it just for the knowledge, I have no desire to go into the interviewing process again. I agree that interviewing is a broken process.

BJanecke 8y ago

There is nothing about learning how basic data structures and algorithms work that won't help you in your day to day development. You might be "fine" without it in a certain category of job, but rather than be dismissive about it you could be excited about having a massive wealth of information that you can use to do your job better. There will always be something else to learn, wether it be how to apply Domain Driven Design to your work or how to work with graphs when munging data. It's always worth it. [edit] Run on sentence

octorian 8y ago
> There is nothing about learning how basic data structures and algorithms work that won't help you in your day to day development. Having a basic understanding of these things is NOT the same as being able to regurgitate them on a whiteboard, under the stress of the interview process.
- LandR 8y ago
  Exactly, I don't need to know this stuff of the top of my head. I can look it up...
  - lordCarbonFiber 8y ago
    The reason we test for things is to verify you have enough domain knowledge to "look it up". A bad interviewer will ask you to write quick sort on the board, because if we've already gotten to the point of "implement quick sort" yeah we can just look that up. However, if you're given a collection of nodes and asked to do something with them; that's a bit more interesting. If you know nothing about graph traversal, or have never seen a tree (both not uncommon in people claiming to be principle engineers in my industry) how do you even know what to search for? Best case is you're smart and waste time coming up with a new solution from first principles; most likely it just never gets done.

gumby 8y ago

> The only reason it seems to even learn them is to pass an interview... While I agree that the process is broken, a solid understanding of algorithms and data structures is very important for developers at my company. And nobody knows all, or even most of the algos or data structures! But we do have large amounts of data and some pretty complex analytic problems, and a poor design can cost a lot of time and AWS $. Likewise over-engineering something small is a waste of time not just in writing but maintaining it. I agree that most e-commerce or business web developent probably don't need this level of formal skill. Whiteboard questions are useful, but not for figuring out trick questions. Instead for figuring out how the candidate approaches problems.

kamaal 8y ago
Those look like software design skills. Also the type of systems you describes use something like Hadoop, and use things like Hive and Pig on top of it. Once you get the data out you use Python or R. And you generally use a standard library to work with. That really SQL + general programming. What new problems are you working on that require you to invent novel algorithmic techniques?
- C4stor 8y ago
  Even after choosing a technology (like Hadoop), there's a lot of difference between the best and the worst algorithm to solve a problem. For example, the reduce phase of MapReduce is pretty much "apply the algorithm you want on this List", and that's where knowing good list algorithms (for example) shine.
  - kamaal 8y ago
    Sorry, in almost all cases its really choosing over several ways of Joining the data, not writing SELECT *, not writing cross joins and learning SQL well. Which why I ask again. Please list your problem which is so novel it requires you to invent a novel algorithm. Please note statistics is a science that has existed for centuries now. Unless you are in a university, its highly unlikely you have a problem that will need to you to work on something that novel.

intkj 8y ago

What better way is there to try and get the best assessment of someone’s coding ability in a 45 minute timeframe?

TomMarius 8y ago
IMO not doing it. Why'd you do it? There are much more important factors than someone's ability to do a whiteboard exercise while under stress. You can e.g. check their Github, ask them to make a simple example project at home, etc.
- sgc 8y ago
  This. Test them using the tools they will be using every day.
LandR 8y ago
You aren't testing their coding ability though you are testing their ability to remember how to implement a very specific algorithm.

fsloth 8y ago

"these are really hard problems that people have studied for years" Because of this. So that when you encounter a problem, you know how it can be solved efficiently. If you disregard existing knowledge, you are likely to spend a lot of time cooking up something complex and half-assed that creates an unnecessary maintenance load. Like music is composed of fundamentals, similarly most problems in computing can be decomposed such that familiar approaches can be applied to them. I think the categorization of Aho's "Foundations of Computer Science" is pretty much to the point on which fundamental formulations are practical to know.

kamaal 8y ago
>>If you disregard existing knowledge, you are likely to spend a lot of time cooking up something complex and half-assed that creates an unnecessary maintenance load. Unless you are stuck on an Island coding during a vacation, not one person on earth faces this kind of a situation. Almost anybody doing anything apart from basic beginner level coding work knows to look up to a solution on the internet if a solution is not scaling already.
- fsloth 8y ago
  "Almost anybody doing anything apart from basic beginner level coding work knows to look up to a solution on the internet if a solution is not scaling already" This applies to some practical areas, but some are murky and need more than agile google-fu to waid through of an algorithmic jungle to a solution that provides added value to end user. There is a discipline and domain dependent threshold where the internet suddenly becomes obscure and unhelpful when one is trying to find solutions. In these instances either you are solving the wrong problem, or the problem is quite complex and/or does not have a closed form/ready solution. The best thing to happen in these instances is that one can limit ones input domain just so that it maps to some algorithmic concept or another. It's not rocket science, but in these instances having an intuitive feel toward the big O behaviour and various algorithmic constructs is really, really helpfull. Sometimes you just need to implement your own fudged QR decomposition and understand a little bit of numerics, or build custom octrees and whatnot. Couldn't really do it without my books. I do CAD and computational geometry stuff, YMMV.