“To me, legacy code is simply code without tests.” — Michael Feathers
If untested code is legacy code, why aren’t we testing data pipelines or ETLs (extract, transform, load)? In particular, data pipelines built in SQL are rarely tested. However, as software engineers, we know all our code should be tested. So in this post, I’ll describe how we started testing SQL data pipelines at SoundCloud.
Once every two weeks, we prepare new versions of our mobile apps to be published to the app stores. Being confident about releasing software at that scale — with as many features and code contributions as we have and while targeting a wide range of devices like we do at SoundCloud — is no easy task. So, over the last few years, we have introduced many tools and practices in our release process to aid us.
In this blog post, I’ll cover some of the techniques we use to guarantee we’re always releasing quality Android applications at SoundCloud.
Memory leaks are a common problem when writing iOS applications, and while we all know we should be on the lookout for them, it’s often too easy to miss a vital weak reference. By leveraging integration testing, we can catch these issues and spend more time actually building features.
At SoundCloud, we follow best practices around continuous delivery, i.e. deploying small incremental changes often (many times a day). In order to improve the user experience, we’ve been exploring different ways of reducing the impact and the Mean Time to Recovery (MTTR) of faulty deployments. Enter canary releases.
Testing mobile applications is not always an easy feat. In addition to defining what to test and determining how to write those tests, actually running tests can also be problematic — in particular, UI test suites running on real mobile devices or emulators sometimes run for an extensive amount of time.
Apple introduced automated UI testing in Xcode 7. This was a great addition for developers because this native support promised, among other things, an improvement in the flakiness notoriously associated with automation tests. As many of us developers have experienced, tests can sometimes fail even when there has been no modification to the test or underlying feature code.