Quality Assurance (QA) processes play a pivotal role in ensuring the reliability and functionality of products in software development. In this journey, test automation metrics emerge as invaluable tools that guide QA teams toward enhanced efficiency, better issue identification, and improved overall performance. By providing insights into the testing process, these metrics facilitate data-driven decisions and empower teams to refine their strategies.
Test automation metrics play a crucial role in the success of QA teams by providing valuable insights into the testing process, helping identify issues, and enhancing team performance.
The correct automation coverage metrics offer an impartial and in-depth view of your QA procedures, enabling you to pinpoint and rectify pain points, all the while boosting efficiency and effectiveness.
During the transition to automation testing, it’s vital to establish a pertinent set of metrics for automation testing to generate insightful data for your automation metrics report. Only when you measure your test progress can your team make full use of the speed, coverage, and efficiency that automated testing provides.
This brings us to a key question: Which test automation reporting metrics should you focus on for a clear view of your processes, and how should you monitor them effectively.
This comprehensive guide delves into the appropriate scenarios for automation testing and outlines the essential metrics you should track, including the decision criteria for sprint automation metrics.
Determining the Right Time for Automating QA Testing
Before diving into the essential metrics for automation testing, it’s imperative to identify the QA tests that warrant automation. Often, a surprising number of manual tests can be completely substituted with automation testing.
In essence, any repetitive test performed frequently across development cycles that don’t necessitate extensive human intervention should be automated. Suitable candidates for test automation include unit testing, component testing, acceptance testing, and GUI integration testing.
Once you’ve identified the tests suitable for automation, you can calculate your Automation Index. This involves tallying the total test cases and then dividing the automatable ones by the non-automatable ones. This outcome provides insights into the resources required for the project, including ongoing QA support.
Why are Automation Testing Metrics important?
In managing DevOps and TestOps, automation testing metrics are valuable tools. They help us keep track of what’s happening in a detailed way, which is really important when things change a lot. Also, these metrics can help companies find and get the right tools for automation testing.
Here’s why it’s good to look at automation testing metrics from the start:
See What’s Happening Now: These metrics give us clear insights about how our software testing is going. We can know how many tests are being done, how many problems are found, and how fast the tests are being done. Check if Automation is Helping: We can use performance metrics to see if using automation testing is really making our app better, or if we’re not getting anywhere. It also shows us where we need to focus more when making the app, to do better testing. Speed Up Testing: By looking at these metrics, we can see how long tests take. Then we can figure out ways to make tests go faster and have a better plan for testing.
Recommended Metrics for Test Automation
The primary objective of measuring performance metrics is to ensure consistency in both products and processes, as well as to assess the optimal utilization of resources. Below are the key test automation metrics recommended by our team.
- Automation Progress
Monitoring test automation metrics over several weeks allows you to gauge your performance against expectations. Incorporating this Key Performance Indicator (KPI) aids in establishing an expected testing rhythm across release cycles.
By analyzing your automation metrics report, you can pinpoint significant deviations in the number of automated test cases. These deviations could stem from tasks being deferred due to higher-priority issues, unforeseen complexities in the product, or ineffective execution of efforts by the team. Identifying the root cause enables resource reallocation and the creation of a new roadmap.
- Percent of Automated Test Coverage
This metric ranks among the most pivotal in automation testing, as it reveals the extent to which your codebase benefits from test automation. Calculating this KPI within your automation coverage metrics provides insights into how close you are to achieving maximum product coverage through automation. This tracking system in your automation metrics report acts as an early warning mechanism, facilitating resource adjustments during live QA processes.
To calculate this metric, apply the following formula:
Percent of Automated Test Coverage = (Automation Coverage / Total Coverage) * 100
- Equivalent Manual Testing Efforts (EMTE)
While there are valid reasons for incorporating manual testing, it inherently operates at a slower pace. This metric quantifies the effort required to execute an automated test case manually, highlighting the time saved across both methods within a release cycle.
EMTE = Length of Time for Manual Testing – Length of Time for Automated Testing
- Number of Defects Found
This KPI tracks the number of issues, bugs, and errors discovered during QA testing. It quantifies the level of software release problems across different cycles and can be utilized for predictive modeling by estimating residual defects under specific coverage levels. A higher count of defects suggests the need for additional resources or indicates coding challenges due to expanded product features.
- Defect Distribution
Knowing the number of defects uncovered during QA may not suffice. Identifying the specific locations of these issues within the codebase helps developers address problems effectively instead of resorting to temporary fixes. Recognizing these problematic areas sheds light on issues beyond development, including problematic requirement gathering, bottlenecks in the development process, and resource inadequacy.
- Script Maintenance Time
Creating test scripts and use cases in line with established goals is an ongoing pursuit for your automation team. However, ongoing maintenance remains necessary during the development phase, despite your efforts to identify elements, formulate data, and verify scripts. This metric gauges the time allocated to maintenance activities, offering an overview of test automation’s overall value for the project.
- Breakeven in Automation
This KPI evaluates the efficiency and Return on Investment (ROI) of employing test automation. Ideally, the manual effort saved should surpass automation efforts by 30-50%, resulting in a positive ROI. This information empowers managers to make informed decisions about the continuation of automated testing. Tracking this metric provides a means to assess whether this approach offers the best ROI for your QA process.
Effective test automation metrics form the backbone of QA processes, offering insights that drive informed decisions. As organizations strive for quality and efficiency, these metrics serve as a compass, guiding them toward a successful QA journey. By leveraging test automation metrics, teams can steer their projects toward success in the dynamic world of software development.
If your team requires assistance in identifying and measuring these test automation metrics, consider collaborating with a QA services provider such as Varseno. Our team of testing experts specializes in both automation and manual testing, boasting extensive experience in conducting test cases across various domains. Allow us to aid your team in identifying your testing KPIs and devising effective means to gauge your QA performance within the development process. Reach out for a free quote today.