Entries by Frank Jung


Using Randomness to Test Code

Using Randomness to Test Code In part 1 of this series, we explored pseudo-random values. These are values that are statistically random, but are derived from a known starting point and is typically repeated over and over. In this article we explore how random values can be used in testing. You may already be familiar […]

GitHub Actions First Impressions

     Introduction In our earlier article on Git pipelines, we mentioned that GitHub had released a beta of Actions, their latest CI/CD workflow automation tool. Let’s take a quick look at some of its features. For simplicity, we’ll use the same example as in the previous article – that of rendering this article into HTML – which is more than enough […]

A Short Introduction to Git Pipelines

Introduction Git has become the de facto standard for version control, but until recently you needed external tools such as Jenkins or GoCD to manage Continuous Integration / Continuous Delivery (CI/CD) pipelines. Now, though, we’re seeing vendors like Gitlab and others providing pipeline features with extensible suites of tools to build, test and deploy code. These integrated CI/CD features greatly streamline solution delivery […]

Some Thoughts on Random Number Generators

Introduction One of the first exercises given to me as a mathematics student was to write a random number generator (RNG) – which turned out not to be so easy. Test sequences cycled quickly, or were too predictable, or were not evenly distributed. Typically, when we talk about RNG’s, we are describing pseudorandom number generators. Nowadays, there […]