[gpderetta]

I'm a lowly c++ software engineer. You might not have to deal with that stuff, but for me it was Tuesday.

Kidding aside, someone has to build those tested, stable libraries that handle those problem (or even untested bleeding-edge if you are breaking new ground).

[rpedroso]

I primarily write python web-based APIs for a web application + 2 mobile apps. Just the other day, I was dealing with an endpoint that had to update hierarchical data (i.e. a collection of trees).

Due to the circumstances, normalization wasn't an efficient option. I ended up throwing together a barebones tree with a 5-line DFS implementation to traverse it. It handled inserts, updates and deletions (for my use-case) in linear time.

The details aren't so important as the fact that adding a dependency would have been overkill for my needs. This isn't to say that efficient graph implementation libraries should not exist or be used, but I was able to produce this code faster by having that basic CS knowledge.

[lordCarbonFiber]

And because your code was implemented in python (rather than use prebuilt libraries that call back to C) it was 100x slower than it should have been. Im all for knowing the fundamentals but there is a strong argument for knowing the right tool for the job.

[joshuamorton]

And because it was attached to a web api, it was likely still io bound, so it didn't matter.

Context and knowing the right tool for the job is important indeed.

[fencepost]

re: the debate between Python being slower and C faster, it all depends on context. If the context is "this is going to be called multiple times for every transaction" then yeah, look into recoding it. If the context is "this is going to be called for this particular edge case and may execute 10 times a week and take an extra 3 seconds each time" then there are more productive places to put your energy.

At the level of programming that the grandparent is talking about, I'd accept the judgement of the programmer working on it as to the appropriate solution.

[quantumhobbit]

Where does one get a job writing actual algorithms and data structures? I actually enjoy that and am pretty good at it. I'm sick of jobs that are nothing but glueing together poorly documented and tested libraries.

[gpderetta]

I'm currently working in finance. Before that I was working at a major search engine which doesn't start with G.

[Silhouette]

Where does one get a job writing actual algorithms and data structures?

Two big areas that come to mind are simulation/mathematical modelling, where you're often crunching data in ways that aren't just textbook examples, and embedded systems, where you often have resource constraints that make efficiency more important.

This doesn't just mean modelling weather systems on supercomputers or writing the control software for cars, though. For example, consider user interfaces. We are increasingly looking for more intuitive input methods using techniques like natural language processing, speech recognition, handwriting recognition, and gesture-based UIs. We are looking for more intuitive output methods, such as integrating additional data with real world imagery like maps or the view through a 3D head set or camera. We are looking for systems that learn patterns in their users' behaviour and adapt to provide more likely options more quickly next time.

You won't see much of this if you're just writing simple form-based web front-ends for CRUD applications. A lot of real world software is like that, and it gets a lot of useful work done, but it's mostly pretty mundane, join-the-dots work as far as the programming goes. However, there are plenty of interesting problems out there and we could directly improve the user's experience in new and helpful ways if we could solve them, and much of that work involve developing data structures and algorithms far beyond anything you'd find in an introductory textbook.

[quadrature]

Data Engineering, SRE, Production Engineering are really good for that kind of thing. Especially at a larger company, but the truth is those opportunities aren't going to come up that often, you don't want to be continuously inventing your own technology unless you're living on the bleeding edge like Google.

[lijason]

Lots of places, but I would guess finance and gaming have it at the highest percentage. They have the strictest performance requirements so algorithms and data structures end up custom built for the job more often.

[zo1]

Game development, and research are the two that come to mind for me.

[duiker101]

This is very true, but I don't think that anyone interviewing for a position like yours will reference to this list of things to test their candidates.