As companies strive to become more agile and move faster, the role of QA is changing. No longer is it enough to simply run tests and find defects; today’s QA teams need to be proactive, working with the developers to ensure that quality is built into the code from the beginning. This requires a different set of skills and a different mindset. Thus, to help QA teams make this transition, many organizations are turning to test automation. Test automation metrics can help QA teams move faster and be more efficient, freeing them up to focus on more strategic tasks. But test automation is not a silver bullet; it comes with its own set of challenges.
One of the biggest challenges with test automation is measuring its success. How do you know if your test automation efforts are paying off? What are the right metrics to use?
In this article, we’ll answer these questions and more. We’ll start by defining what test automation metrics are and why they’re important. Then we’ll dive into 10 key metrics and KPIs that every QA team should track.
What Are Test Automation Metrics?
Test automation metrics are performance indicators that can be used to measure, track, and optimize the effectiveness of your test automation strategy. By understanding how well (or how poorly) your testing efforts are performing, you can adjust your process and tooling choices to improve efficiency and quality.
There are two main types of test automation metrics:
- Those that focus on process, and
- Those that focus on product quality.
Both are important, but product quality is usually the primary concern. After all, the point of testing is to find defects before your users do! However, one should not ignore process metrics. They can also give you important insight into how well your team is working together, and where bottlenecks are occurring. By understanding and improving your process, you can make your testing more efficient and effective.
Challenges With Test Automation Metrics and KPIs
There are a few challenges that can make it difficult to collect accurate test automation metrics.
First, it can be hard to define what constitutes a “defect.” For example, is a cosmetic issue that doesn’t affect functionality a defect? Is a minor usability issue a defect? These questions don’t have easy answers, and different teams will have different standards. This can make it difficult to compare metrics between teams or projects.
In addition, it can be difficult to attribute defects to specific tests. For example, if a test fails but the defect is actually caused by an issue in the code, it’s not really a “defect” in the test. This can make it hard to determine how effective a test really is. Finally, it can be challenging to collect accurate data. For example, if tests run manually, it’s hard to track how often they’re actually run. In addition, if tests are run on different machines or in different environments, it can be difficult to compare results.
10 Key Test Automation Metrics and KPIs
To help you begin, here are 10 key test automation metrics and KPIs that every QA team should track:
1. Code Coverage
Code coverage is a measure of how much of the code is actually being tested by the automation. A higher code coverage percentage indicates that more of the code is being tested, which means that there are fewer untested areas of the code.
2. Pass/Fail Rate
The pass/fail rate is a measure of how often the tests are passing or failing. A higher pass rate indicates that the tests are more stable and less likely to find defects. However, a lower pass rate may indicate that the tests have become outdated or not comprehensive enough.
3. Test Execution Time
Test execution time is a measure of how long it takes for the tests to run. A shorter execution time indicates that the tests are faster and less likely to slow down the development process. A longer execution time may indicate that the tests are too slow or not well-designed.
4. Test Case Count
The test case count is a measure of how many test cases there are. A higher test case count indicates that the tests are more comprehensive and less likely to miss defects. However, a lower test case count may indicate that the tests are not comprehensive enough.
5. Test Automation Metrics Suite Size
Test suite size is a measure of how many test cases there are in the automation suite. A larger suite size indicates that the tests are more comprehensive and less likely to miss defects. Further, a smaller suite size may indicate that the tests are not comprehensive enough.
6. Test Case Pass/Fail Ratio
The test case pass/fail ratio is a measure of how often the test cases are passing or failing. A higher ratio indicates that the test cases are more stable and less likely to find defects. A lower ratio may indicate that the test cases have become outdated or not comprehensive enough.
7. Test Suite Pass/Fail Ratio
The test suite pass/fail ratio is a measure of how often the test suites are passing or failing. A higher ratio indicates that the test suites are more stable and less likely to find defects. A lower ratio, however, may indicate that the test suites have become outdated or not comprehensive enough.
8. Defect Density
Defect density measures how many defects occur per unit of code. A higher defect density indicates that more defects occur in the code. A lower defect density may indicate that the tests are not comprehensive enough.
9. Mean Time to Repair
Mean time to repair is a measure of how long it takes to fix the defects that are found. A shorter mean time to repair indicates that professionals fix the defects faster without slowing down the development process. Further, a longer mean time to repair may indicate that professionals have not fixed the defects fast enough.
10. Test Effectiveness
Test effectiveness is a measure of how well the tests are finding defects in the code. Higher test effectiveness indicates that the tests are more effective at finding defects. Lower test effectiveness may indicate that the tests are not comprehensive enough or that they are outdated.
Learn More About Test Automation Metrics
These include just a few of the many metrics and KPIs used to measure the success of your test automation. The key is to find the ones that are most important to your organization and track them over time. By doing so, you will be able to see how your test automation is performing and make improvements as necessary.
Appsurify is the leading provider of test automation solutions. TestBrain is our Risk-Based Testing Tool that delivers test results on a per-change basis and tightens the feedback loop between QA and Development. Schedule a demo to see how we can help you release better software, faster, and more confidently.