If you ignore the terminology, DFS is basically just recursively walking a graph, something which actually happens all the time in most dev jobs. I'm sure I wrote a DFS long before I had heard the term.

I hate brain teaser interviews as much as the next guy, but being able to do basic operations on basic data structures is pretty much the minimum to be a developer.

> If you ignore the terminology, DFS is basically just recursively walking a graph, something which actually happens all the time in most dev jobs.

In ten years of full-time professional development I have never needed to recursively walk a graph. Hell, the only data structures in the software I worked on for the first six (real-time signal processing code) didn't use any data structures other than lists, arrays, and C structs. I would not be able to answer the interview question that started this subthread, despite my track record of efficient and well-designed code.

Are you sure? Keep in mind that a graph doesn't always come up and slap you saying that it's a graph.

This very comment thread is a graph which is being printed depth-first.

I'm very sure. The signal processing code had no graph structures whatsoever.

That's certainly not the case with the NLP code I have been working on for the past 4.5, but I have never personally needed to search the (usually) trees in a structured manner. Most of our code that searches for things doesn't care about the structure of the graph during the search; it just searches a node list. Once the node is found, structure matters. There are some algorithms that use calculations like shortest path and tree height, but I didn't write the code to actually do that.

Do you think you've ever had to do something as algorithmically complex as recursively walk a graph?

Sometimes these questions are used to probe the meta understanding of a candidate and using Graphs/Trees/DFS are universally understood concepts that make doing that easy.

Define "algorithm". In the broader definition, yes. Kalman filtering, motion compensation, track association, XY-mapping, and similar signal processing algorithms. For NLP it has been various forms of statistical modeling and general multithreaded architecture and coordination.

As for the algorithms typical of computer science, not really. Searching and sorting has not been much a part of what I have done. My experience is mainly in translating math into code, often into code with real-time deadlines.

It only stumped the candidates that clearly wouldn't make it through the rest of the problem. One sixth was a probably a high estimate.

DFS for an acyclic graph is about five lines of code and shows me that you A. know a programming language B. can figure out a data structure. I would argue both are needed to perform a dev job.

I've written DFS about 1-2 times a year, on average, for the last 15 years. Why do I need to? Usually, because I need to modify or create a data structure that is kind of graph-like but not quite. If someone didn't know how to write one or at least derive it, they would confuse a lot of people, so yeah it's kind of important.

No, they'd probably look it up, skim a blog for a few minutes, then figure it out and promptly forget. This is no different than forgetting the order of the arguments to socket() and accusing that person of being incapable of writing networking code.

The difference is that the arguments to socket() were arbitrarily defined, but DFS is an algorithm. Anyone who has taken a intro data structures course should be able to at least derive the pseudo code for DFS.

Eh, I had to write a DFS the other day at work.