Complete and exhaustive testing is not possible. Nor would it be fun, or maintainable, or a good use of your time.

However, some functionality is important enough to make sure the test behavior coverage is thorough enough to have high confidence in it's quality.

In this episode, we discuss 3 techniques that can be combined to quickly generate test cases. We then talk about how to implement them efficiently in pytest.

The techniques covered are:

We discuss how to use these to generate test cases for a new list filter functionality in the cards application.

The resulting tests:

Sponsored By:

• Python Testing with pytestSimple, Rapid, Effective, and Scalable

Support Test & Code - Software Testing, Development, Python

Links:

• github cards project (version 0.1.11)
• Equivalence partitioning - Wikipedia
• Boundary-value analysis - Wikipedia
• Decision table - Wikipedia
• Slack Channel for Test and Code
• DJ YANiC - The awesome listener that contributed our theme music.