Test automation brings efficiency and reliability to software testing, which is especially important in today's Agile environment.
However, it is not enough to simply run automated tests and incorporate them into your CI/CD pipelines. It is also important to measure their effectiveness to ensure that test automation consistently delivers value to your business!
There are several key performance indicators (KPIs ) that measure the success of your automated tests, and in this article, we'll review the top 5 metrics to track in your test automation to get the most out of your efforts.
Why do we need metrics for automated testing?
The main purpose of KPIs is to demonstrate the performance of the testing process.
When it comes to deciding which KPIs to measure, it's important to ask yourself why you want to measure automation quality in the first place. :
Quantified results
Building an automation suite to quickly deliver new quality features to customers takes time and resources.
KPIs can be used to track the effectiveness of automated testing over time, helping you achieve the goal of becoming exponentially agile and getting a quantified return on investment.
Accelerated time to market
If you want to speed up your release times, you need to know how fast you're moving first!
KPIs can help speed up the testing process by highlighting areas that are not progressing as expected.
Hold your QA team accountable in a specific way
Having a standard set of consistently communicated KPIs will allow you to hold your team accountable for problems in different parts of the testing process.
Continuous improvement
Getting better over time should be a goal for any organization.
Measuring the progress of your tests will help you adjust and overcome challenges as you improve your scripts and automation processes.
Test automation - Top 5 indicators to follow
1. Automatable test cases
Not everything can be automated!
A key feature of the test strategy is to prioritize automation for those test cases that will provide the greatest return on investment.
This metric can help teams prioritize high-value areas for automation and identify areas that still require manual, exploratory testing.
*Splitting this metric to cover specific components of your application can provide an even higher value.
Automatable test cases % = (# of automatable test cases / # of total test cases) * 100
2. Progress in automation
This KPI refers to the number of automated test cases that have been executed at any given time.
It is used to track the progress of an organization's automated testing efforts over time and identify where additional automation is needed to improve testing efficiency.
For example, if your goal is to automate 100% of "automatable" test cases, this KPI can be used to track your progress towards that goal and identify if there are significant deviations during the testing process.
Deviations" can include tasks that are put on hold due to other priorities or unforeseen items in the software, for example.
This metric can also be measured against the automation goal of a regression suite or new feature to help you understand when progress is being made.
Automation progress % = (number of real automated test cases / number of automatable test cases) x 100
3. Test coverage
Test coverage tracks the number of test cases performed and illustrates the percentage of test coverage performed automatically versus manually.
By measuring this KPI, you can understand how well your code base is covered by all types of automation and reveal the parts of the software that do not have sufficient test coverage.
Automated test coverage % = (# of automated tests / # of total tests) *100
4. Density of defects
Defect density measures the total number of bugs and errors discovered during a development cycle.
This KPI identifies the weakest parts of the software that require more rigorous testing, and also reveals whether the development phase presents coding challenges that require more resources or training.
Defect density = (number of known defects / total system size) *100
5. Success rate
Representing the percentage of successful automated tests, this metric is useful for understanding the stability and effectiveness of your automated test suite.
Having a low pass rate requires more time spent validating failures. If the failures turn out to be false failures, it is an early indicator that your tests are unreliable.
If you see this number drop after an automated test run, it will serve as an indicator that your version contains a higher than normal number of defects.
Success rate % = (# of successful cases / # of executed test cases) * 100
Automated test KPIs - don't lose sight of the big picture
KPIs are very useful if they are aligned with your automation strategy, to guide you in your strategic decision making.
However, don't become too fixated on achieving positive goals. When a metric becomes the goal, it ceases to be a measurement!
Another thing to consider is that while metrics are essential for tracking and understanding test automation, each one can show an incomplete and sometimes misleading picture.
This means that it is extremely important to take into account the context and to analyze each KPI with a sharp eye.
Mr Suricate | Informed automated testing KPIs
The no-code automated testing tool from Mr Suricate automated testing tool provides several indicators to measure the performance of your tests.
Its intuitive UX and clear reporting simplify the identification of the indicators to be followed in test automation.
