Test-reduction - Doing more with less

What if a tool injected bugs into your code to see if your tests could find them? Learn how mutation testing reveals your true test quality.

#1about 2 minutes

Why developers often view unit testing as a chore

Unit testing is often treated like a necessary but undesirable task, which raises the question of when enough testing has been done.

#2about 3 minutes

Distinguishing between code coverage and test coverage metrics

Code coverage is a quantitative metric measuring how much source code is executed, while test coverage is a qualitative metric assessing how well tests cover possible scenarios.

#3about 3 minutes

Using mutation testing to measure test suite quality

Mutation testing automatically introduces small bugs (mutants) into source code to verify that the existing test suite can detect and "kill" them.

#4about 3 minutes

Applying basic test design with the error guessing technique

Error guessing is an intuitive, experience-based technique that is good for covering happy paths but often misses important edge cases.

#5about 3 minutes

Structuring tests with the decision table technique

The decision table technique systematically covers all combinations of input conditions but becomes impractical as the number of conditions grows exponentially.

#6about 7 minutes

Generating effective test cases with property-based testing

Property-based testing generates a wide range of test inputs automatically by describing data properties rather than specifying concrete examples, excelling at finding edge cases.

#7about 2 minutes

Prioritizing test efforts using risk-based testing

Risk-based testing helps teams decide how much testing is sufficient by estimating the probability and impact of potential failures to focus efforts on high-risk areas.