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Published August 4, 2022

The Importance of Automated Regression Testing with Social Integration in DevOps

The Importance of Automated Regression Testing with Social Integration in DevOps

Delivering business-critical applications and code relies on two key factors; functionality and efficiency. Mock and Unit tests are a few industry standards that aim to ensure the correct functionality of your code, catching potential bugs and issues before deployment. These tests are vital to workflows, CI/CD pipelines, and the overall build and deployment process. While functionality may be sound, one key aspect that is oft-forgotten is the efficiency and performance of your code. While your team’s latest build may have finally fixed various bugs that persisted through multiple deployments, it is just as important to ensure the performance of your application and code were not affected by the changes. Even small, non-noticeable changes in performance can have a trickle-down effect, where they may not be realized until several builds later, up to a point where finding and fixing the initial cause of lost performance becomes a large, time-consuming task. Similar scenarios lead to valuable resources, such as time, being divergently allocated.

One way to prevent these scenarios is to actively benchmark the performance of your code. Doing so allows you or your team to catch any potential slow-downs or inefficient code before it is shipped and deployed. By incorporating benchmarking into your build process or pipeline, you will be able to analyze and notice trends of performance regression and implement the necessary changes to preserve or even increase the performance of your code. This extends to all different aspects of your project, whether it’s the performance of various third-party libraries your project uses or the actual logic/approach implemented in your code, performance can be measured via benchmarking. Correctly set-up benchmarks work similarly to unit/mock testing, and can be inserted into any CI/CD pipeline, meaning your code will be tested for both functionality and efficiency, automatically.

Beyond testing for functionality and performance, there are more aspects to autonomous delivery of projects and code, such as communication and notifications. Manually checking the results of your build is always an option, but for the best efficiency of the CI/CD practice, why shouldn’t notifications and communication be autonomous too? When certain unit/mock tests fail or performance regression is found with benchmarking, the proper team should be notified instantaneously and automatically. You, or members of your team, should be notified immediately of what failed/regressed to ensure that a proper fix is worked on and implemented as soon as possible.

Introducing the benchmark process into your CI/CD pipeline may seem like a big task, especially for established products or larger enterprises, but CyBench bridges this gap by severely reducing the time and effort of implementing proper benchmarks into your autonomous build cycle. CyBench includes a suite of tools, including IDE plug-ins, and plug-ins for build automation tools (such as Maven and Gradle), and even a tool to automatically convert unit tests into benchmarks. All of these tools are suitable for autonomous build cycles. Beyond the tools is the CyBench UI, where results can be viewed and compared in depth. CyBench also features social integrations such as Slack and Zoom, so you or your team can always be updated on the latest changes in the performance of your code. You can learn more about CyBench by visiting its wiki, which includes text and video tutorials ranging from getting started, to implementing CyBench tools into your CI/CD.

You can read a previous blog post on Continuous Performance Regression Testing for CI/CD here.