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Recently, Stack Overflow — truly a software engineer’s best friend — released their annual developer survey which offered insightful takeaways on the current state of working developers and their feelings towards everything from programming languages to the what kind of environment they look for in a workplace. I had blast going through the results and wrote up a fun article to relay my own takeaways from the results which we published here in April.

Now, Stack Overflow has released all of their raw data for us to comb through and reach our own conclusions. With over 90,000 developers taking part in the survey, it is a great dataset to be further analyzed beyond the initial results that Stack Overflow released.

So, it is incredibly fortunate for all that Stack Overflow decided to team up with Glitch to publish and highlight the data.

If you are not familiar with Glitch and the services they provide, Glitch is an online service that allows users to build collaborative apps for a myriad of purposes and then share them through the online community provided. Apps can be customized, personalized, extended, and “remixed” to add functionality or change the display of data. Apps are created and then shared free of charge to streamline work processes, play games, and even create VR experiences. The apps are not relegated to those of us with knowledge of software development, as they can be customized and tinkered with through easy to use UI tools. Changing the output of data is as simple as changing cells on a spreadsheet.

For that reason, Glitch is a perfect tool to provide as a means of diving deeply into the Stack Overflow raw data. Glitch themselves built a handful of apps to display different results than the official survey, and they also went ahead and provided a simple and easy-to-use interface for pulling data based on a handful of different factors such as race, gender, and sexual orientation.

Glitch has provided us with some fun, aggregated charts to analyze a greater cross-section of the survey results by using Chart.js, a simple JavaScript library for creating visualizations from data.

Let’s check some out!

Linux Good, WordPress Bad

As a surprise to no one, developers surveyed on their platform preferences by Stack Overflow are not fans of WordPress. Maybe it’s the entire ecosystem of WP, or maybe it’s just that PHP reads like ancient Aramaic, but apparently, software engineers dread the content management system more than any other option. On the flip side, Linux is loved by most. But that’s what generally happens when your mascot is an adorable penguin named Tux.

Just try not to love that face.

I’m a Bit Rusty When it Comes to Programming

If you thought this was an image to illustrate software engineers’ affinity for a video game where naked cavemen club each other to death in the means of survival, I’m very sorry to disappoint you. (Well, not really.)

Rust is a (relatively) new language created to focus on safety. While syntactically similar to C++, it was designed for better memory safety while retaining a high performance. Because of those reasons, it has become a darling of the development community with the most developers surveyed professing their love of the language created to design better systems. We touched on how far along Python has come along in the previous piece linked above, but this chart really illustrates how well Rust has been received in the development community since it’s release.

On the other hand, as an ex-Ruby developer, I feel personally attacked. Apparently not many developers these days share my love of the word “end.”

Waiting (on) Tables

These data visualizations presented above are just a small subset of the questions asked and the data available to be presented. Personally, I found the SQL interface to be the highlight of the features provided by Glitch for the data retrieval process. In this specific query, all of the data for questions asked are queried and returned, giving an easy way to correspond questions with the columns that hold their data. By providing a simple text box for entering queries, anyone with even a rudimentary understanding of SQL can get started with returning any of the data grouped and ordered to their heart’s content.

A few of the survey questions and responses were barely touched on in the Stack Overflow piece when the survey was released, so it was a lot of fun to dig into the possible answers queryable by the UI tool. For instance, one questions presented was “Have you ever been asked to solve FizzBuzz in an interview?” For those of you unfamiliar with one of the most popular “intro to algorithms” questions, FizzBuzz is a problem that asks you to return numbers with a modulo of zero for 3, 5, and 15. Well, actually it asks you to return “Fizz”, Buzz”, and “Fizzbuzz” for those respective numbers. It is a problem I have given countless students as their initial toe-dipping into the world of algorithms, and despite its oversaturation, it does find itself being used as an interview question every so often when sitting down with Jr. Developers.

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Only second to “foo” and “bar” in its oversaturation.

I, myself, when interviewing for one of my first front-end jobs was presented with the time-honored problem rearranged to return the words “Coke”, “Pepsi”, and “Iced Tea.” I recognized it immediately and despite my questioning the difficulty of the subsequent job if I did pass the interview, it blew me away that I had actually encountered the popular and simple problem in the wild. I was happy to see that it had made its way into the Stack Overflow survey as a question, so I forwarded this to all of my ex-students to show them that they shouldn’t always fear interviews because, who knows, you might just wind up getting FizzBuzz on there.


It was a great experience getting a chance to dive deeper into the data than initially presented by the first release of the annual survey. More so, it is encouraging to see the tools presented to data analysts and data visualization experts for the means of presenting their findings. These days we have a wealth of tools at our disposal for analyzing data in a quick and conclusive fashion. My next step is to download the CSV files and run them through Tableau to see what I can come up with. Whether it ends up as simply some beautiful interactive bar charts and map visualizations remain to be seen, but I can tell you this much: I’m going to have a blast doing it.

If you decide to download the data and come to your own conclusions, we’d love to head about whatever you come up with. Please send us an email at hello@kloudless.com with anything you find interesting!


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