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In part one, we achieved 100 percent coverage. In this installment, we mutate our code and check how good our tests are.

There are several mutation testing frameworks. In this case, we will use PITEST.

Source de l’article sur DZONE

I work as a DevOps engineer for a large public-facing application, which has around 90+ microservices (Java-based). Consistently, we are hit by scenarios that we’d discover in the field, which were not caught in any of our testing. Despite improving our test strategies and code coverage assessments, we were unable to assess the "strength" of our test cases.

We looked around for options and solutions that could help us to be more sure about our test cases and the code we develop. As a DevOps engineer, my responsibility was to identify options and trial them to fix this problem and include it as part of our automated build process.

Source de l’article sur DZONE