Automation Metrics is very imp for Automation QA and SDET, if you are trying for SDET role do check out our post on SDET Job Roles & Responsibilities

As automation testing becomes increasingly popular, it's essential to have a set of reliable metrics to track and measure its effectiveness. In this post, let's take a closer look at some common types of automation test metrics:

Test Coverage:
This metric measures the percentage of code or features covered by automated tests. It helps to identify areas where testing is lacking, enabling teams to add tests to ensure better coverage.

Test Coverage = (Number of Features Covered by Tests ÷ Total Number of Features in the Application) x 100
For example, let's say your application has 10,000 lines of code, and your automated tests cover 7,500 lines of code. To calculate the test coverage, you would plug in these values into the formula:

Test Coverage = (7,500 ÷ 10,000) x 100 = 75%

So, in this example, the test coverage is 75%, indicating that 75% of the application's code is covered by the automated tests.
Tracking test coverage over time can help you identify areas where your tests may be lacking and prioritize efforts to improve test coverage in those areas. It's important to note that test coverage alone is not enough to ensure that your tests are effective, but it is an important metric to track to ensure that your tests are comprehensive.
Test Execution Time:
This metric measures how long it takes to execute automated tests. By tracking execution time, teams can identify tests that take too long to run and optimize them accordingly.
Test Failure Rate:
This metric tracks the number of failed tests and helps teams to identify the areas where defects are occurring most frequently. By analyzing failure patterns, teams can focus on addressing the underlying issues.

Test Failure Rate = (Number of Failed Tests ÷ Total Number of Tests Executed) x 100
For example, let's say you executed a total of 100 automated tests and 10 of those tests failed. To calculate the test failure rate, you would plug in these values into the formula:

Test Failure Rate = (10 ÷ 100) x 100 = 10%

So, in this example, the test failure rate is 10%, indicating that 10% of the tests executed during the period resulted in failures.
Tracking the test failure rate over time can help you identify trends and patterns in your testing process. High failure rates may indicate that there are issues with the application code, or that the tests themselves need to be improved. Conversely, low failure rates may suggest that the tests are not comprehensive enough or that there are issues with the testing infrastructure.
Test Effectiveness:
This metric measures how effective automated tests are in identifying defects. It's important to track this metric to ensure that the tests are providing the expected results.

Test Effectiveness = (Number of Defects Found by Tests ÷ Total Number of Defects Found) x 100

For example, let's say you discovered a total of 100 defects during your testing process, and your automated tests found 70 of those defects. To calculate the test effectiveness, you would plug in these values into the formula:

Test Effectiveness = (70 ÷ 100) x 100 = 70%

So, in this example, the test effectiveness is 70%, indicating that 70% of the defects were found by the automated tests.

5. Defect Leakage:

This metric tracks the number of defects that are missed by automated tests and are discovered later in the development process. It helps teams to identify areas where tests need to be improved or enhanced.

Defect Leakage = (Number of Defects Found after Release ÷ Total Number of Defects Found) x 100

For example, let's say you discovered a total of 100 defects during your testing process. After the product was released, you found 10 additional defects that were not caught during testing. To calculate the defect leakage, you would plug in these values into the formula:
Defect Leakage = (10 ÷ 100) x 100 = 10%
So, in this example, the defect leakage rate is 10%, indicating that 10% of the defects were not caught during the testing process and were found after the product was released.
It's important to track defect leakage to identify areas where your testing process may be lacking and to make improvements to prevent defects from leaking into production.

These are just a few examples of the types of automation test metrics that can help teams to monitor and measure their testing efforts. By using these metrics, teams can identify areas of improvement, optimize their testing processes, and ultimately deliver better quality products to their customers. #automationtesting #testmetrics #qualityassurance

To calculate Test Estimation, check the link below:
Automation Test Estimation

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