This plan focuses on evaluating test performance using various key metrics. By emphasizing metrics like Test Coverage and Defect Density, the plan aims to ensure that more parts of the codebase are tested and fewer bugs are present. For example, a high test coverage ensures that most functionality is being verified automatically, which reduces the risk of undetected bugs.
Test Execution Time and Code Churn Rate are crucial for maintaining efficient and stable code. Shorter test execution times mean developers can get faster feedback on their changes, improving productivity. Meanwhile, managing code churn ensures that changes are necessary and well thought out, minimizing the chances of introducing new defects.
Finally, User Reported Defects highlight the importance of understanding software performance in real-world usage. By keeping these defects to a minimum, the plan seeks to maintain high user satisfaction and software reliability.
Top 5 metrics for Evaluating Test Performance
1. Test Coverage
Measures the percentage of the codebase tested by automated tests, calculated as (number of lines or code paths tested / total lines or code paths) * 100
What good looks like for this metric: 70%-90% for well-tested code
How to improve this metric:- Increase automation in testing
- Refactor complex code to simplify testing
- Utilise test-driven development
- Regularly update and review test cases
- Incorporate pair programming
2. Defect Density
Calculates the number of confirmed defects divided by the size of the software entity being measured, typically measured as defects per thousand lines of code
What good looks like for this metric: Less than 1 bug per 1,000 lines
How to improve this metric:- Conduct thorough code reviews
- Implement static code analysis
- Improve developer training
- Use standard coding practices
- Perform regular software audits
3. Test Execution Time
The duration taken to execute all test cases, calculated by summing up the time taken for all tests
What good looks like for this metric: Shorter is better; aim for less than 30 minutes
How to improve this metric:- Optimise test scripts
- Use parallel testing
- Remove redundant tests
- Upgrade testing tools or infrastructure
- Automate test environment setup
4. Code Churn Rate
Measures the amount of code change within a given period, calculated as the number of lines of code added, modified, or deleted
What good looks like for this metric: 5%-10% considered manageable
How to improve this metric:- Emphasise on quality over quantity in changes
- Increase peer code reviews
- Ensure clear and precise project scopes
- Monitor team workload to avoid burnout
- Provide comprehensive documentation
5. User Reported Defects
Counts the number of defects reported by users post-release, provides insights into the software's real-world performance
What good looks like for this metric: Strive for zero, but less than 5% of total defects
How to improve this metric:- Enhance pre-release testing
- Gather detailed user feedback
- Offer user training and resources
- Implement beta testing
- Regularly update with patches and fixes
How to track Evaluating Test Performance metrics
It's one thing to have a plan, it's another to stick to it. We hope that the examples above will help you get started with your own strategy, but we also know that it's easy to get lost in the day-to-day effort.
That's why we built Tability: to help you track your progress, keep your team aligned, and make sure you're always moving in the right direction.
Give it a try and see how it can help you bring accountability to your metrics.
