Software engineering teams are a critical component of many companies, where the effectiveness of these teams can have a significant impact on the company's success. Making investments in areas such as these in improving developer productivity will pay off significantly, giving development teams more time to focus on …

We've all seen it, code comments that are so obvious they add nothing but noise to the codebase. Redundant comments restating exactly what operation the code is performing. For example, this function's purpose is obvious from its name - adding a comment as well doesn't add any value: 1// Verifies if the auth token is …

Code coverage - how many code lines and branches are accessed during a test - is easy to measure in many languages and test frameworks. And at first glance, measuring code coverage seems like a no-brainer. After all, who wouldn't want to make sure their code is sufficiently tested? But just because a metric is easy to …

The OpenTelemetry Java instrumentation agent automatically instruments many common frameworks but there are times you may want to customize your application's telemetry by adding your own custom spans, adding attributes to existing spans, etc. In that case, it can be helpful to verify the custom instrumentation through …

In this post we'll go through my initial journey to add observability to the Projektor test reporting app using OpenTelemetry and Honeycomb. Projektor already has traditional monitoring with metrics around p95 response times for each REST endpoint, counters for successful and failed operations, etc. But I was intrigued …

Recently I was working on sorting rows in a table in React and I wanted to be able to verify the rows sorted into the correct order. The table shows flaky tests (that is, tests that intermittently fail) and is built with Material Table. Material Table conveniently supports sorting out of the box by clicking on the …

After I added the ability to collect and store code coverage stats in the Projektor test reporting tool, I wanted to also add a graph that showed the trend of code coverage over time. Then users could track their repo's code coverage to see if was increasing, decreasing, or staying the same. The Projektor UI is built …