From The Pipeline v34.0

This entry is part [part not set] of 36 in the series From the Pipeline

The following will be a regular feature where we share articles, podcasts, and webinars of interest from the web.

How Much Testing is Enough?

The google testing blog recently posted details on the scope of their internal testing practice. In addition to defining core terms, they briefly outline their testing: (1) Document your process or strategy; (2) Have a solid base of unit tests; (3) Don’t skimp on integration testing; (4) Perform end-to-end testing for Critical User Journey; (5) Understand and implement the other tiers of testing; (6) Understand your coverage of code and functionality; (7) Use feedback from the field to improve your process.

Test Automation Strategy Guide

Julia Pottinger posted some excellent thoughts on the approach teams should take for test automation. Every team should start with their goal in mind. Once that is determined, teams should identify the tools and techniques for automation. This is followed by identifying who is writing the automation, when it will be executed, and the environments to be used.

What Makes a Good Automated Test?

Kristin has provided a set of guidelines for determining a good automated test. First, tests should be meaningful. This is because each test you write is an investment in the maintenance of that test. Tests should also be maintainable – the automated checks should be readable and well-organized. Tests should also run quickly in order to provide fast feedback for teams.

The Test Data Bottleneck and How to Solve It

Test data is one of the major bottlenecks in testing processes. By simplifying test data, we can solve this bottleneck by tackling four major challenges: Time, People, Size, and Money.

GitHub’s Engineering Team has moved to Codespaces

Recently the GitHub development team shifted to Codespaces for the majority of GitHub development. They’re making this change because local development was brittle — any changes to a local environment could make it useless and require hours of development time to recover. Collaborating on multiple branches across multiple projects was painful. Now, Codespaces executes a shallow clone and repository history in the background, which reduced time to clone. They also created a GitHub Action that would run nightly, clone the repository, bootstrap dependencies, then build & push a Docker image of the result.

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