Coverage Said 69%, Mutation Testing Said 25%
📰 Dev.to · Jeremy Longshore
Learn why code coverage metrics can be misleading and how mutation testing provides a more accurate measure of code quality
Action Steps
- Run a code coverage tool to measure line coverage
- Configure Stryker for mutation testing
- Compare the results of code coverage and mutation testing
- Identify areas of code that require improvement
- Apply mutation testing to critical components like rules engines
Who Needs to Know This
Developers and QA engineers can benefit from understanding the limitations of code coverage metrics and the value of mutation testing in ensuring code reliability
Key Insight
💡 Code coverage metrics do not necessarily reflect code quality, and mutation testing can reveal weaknesses in code that coverage metrics miss
Share This
🚨 Code coverage metrics can be misleading! 🚨 Use mutation testing for a more accurate measure of code quality #mutationtesting #codecoverage
Key Takeaways
Learn why code coverage metrics can be misleading and how mutation testing provides a more accurate measure of code quality
Full Article
A repo at 69% line coverage scored 24.88% on mutation testing—and the rules engine that touches user email scored 0.00%. Coverage said fine; Stryker didn't.
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