Challenges Setting the Right QA & Testing Metrics
Management of the development processes in project teams relies on metrics. Meanwhile, software testing quality metrics can be a massive undertaking, especially when it comes to tracking results. There are also other difficulties that QA teams face such as:
- getting sufficient test coverage across different systems;
- lack of technical proficiency;
- inadequate teamwork;
- ineffective use of tools and resources;
- unclear objectives;
- and incorrect estimations.
If you have no system in place to assess the productivity, efficiency, and effectiveness of your QA team, implementing a few basic quality assurance metrics is a good place to start. Alternatively, you can improve on your current metrics to discover additional areas that need fixing as well as find bottlenecks. Either way, the value of metrics is evident, and it is unlikely that software testing can be accurately gauged without the use of QA metrics and reporting.
Metrics in Software Testing: How Are They Helpful?
How to Improve on Your QA Metrics in Software Testing
QA metrics are all about consistency and doing the same things repetitively while constantly refining your methods to achieve the best results. Basically, it comes down to track, track, and then track some more. Don’t stop recording QA metrics after you’ve started. But monitoring metrics does not have to be a laborious manual task as you can automate data gathering to save more time, and ensure the metrics are always useful for constant improvement.
Furthermore, tying a metric to a QA KPI can really assess a testing team’s efforts based on a variety of criteria. It provides greater transparency into performance statistics that can be used to improve team cohesion, progress, and skills, and workflow efficiency.
QA Metrics to Track
When a metric gives a team a goal, it also motivates them to ask questions, rethink its design, rethink testing approaches, and more. Different teams have different quality benchmarks, so it is about finding the right metrics that suit your specific needs.
You can learn about the most commonly used QA metrics in our previous materials. In particular, you can find different categories of metrics and formulas for each in the video:
In this article, we’ll tell you about five more parameters that will be useful to track, especially if you are reviewing your current metrics and look for more effective ways to monitor the team’s performance. These are:
- Quality of test documentation.
- Test reliability.
- Time to fix.
- Defect distribution.
- Defect leakage.
Now, let’s take a look at each.
Quality of Test Documentation
The artifacts produced before or during the testing of software are recorded in test documentation. The testing team can predict testing requirements, test coverage, resource tracking, execution, and production progress. The QA services always include describing and documenting test strategies, test designs, and test results that are derived from the testing activities all based on a comprehensive suite of documents. So, how do you measure the quality of the test documentation?
Firstly, to track if QA engineers are running successful and high-value test cases, measure the effectiveness of a test case to detect bugs. Review the difference between the number of bugs picked by one test versus the total number of bugs found in the app or website. A high percent indicates higher test effectiveness and lower maintenance efforts required on the test cases.
Quality of Test Case = Number of bugs detected in AB Test / Total bugs in all tests + after release) X 100
Test Reliability
Testers often focus on the mere satisfaction of completing all the tests but that does not guarantee they are reliable. Running a Test Reliability metric refers to the number of test cases that are not providing useful feedback deeming them unreliable. An unreliable unit test is not deterministic and may pass or fail for no identifiable reason.
In an ideal world, a failed test always includes a real bug, and tests would only pass when no defect is present. To measure the reliability of your test suite, determine how often tests are failing without the presence of valid bugs. If it is frequent, then the issue could lie with the test. It may reveal poorly written tests (for whatever reason), test environment failures, or another problem that helps in identifying patterns and recognizing where changes are needed.
Time to Fix
There are several process metrics that can quantify and track metrics around how quickly and thoroughly teams are resolving issues. Take the date the bug was opened until the time it is resolved (and passed QA). Extend the metric to include time taken from the date the bug was opened until it is deployed to production – this can measure how long the users are waiting for a fix. The bugs can be filtered by severity and these process metrics give you a better idea of the efficiency of the different stages of development.
Alternatively, track the number of bugs that have been active for more than 24, 48, or 72 hours. It is important to look for trends and analyze how promptly bugs are being resolved according to priority. Furthermore, it can also detect how many bugs have persisted in the software over time.
Defect Distribution
Defect Distribution is the count of defects in a sprint or particular area of functionality. This metric can provide a better view about the spread of bugs and highlights the overall quality of coding in different teams and different features. A high number of bugs, especially those with high priority may indicate more peer and code reviews are needed and it can point out the parts of the software that are problematic and require redesign or more testing.
Metrics for Defect Distribution can include the percentage or number of defects distributed by priority, module, testing team, and so on. After making the necessary changes in weaker areas of the product, this metric can be run after each build or testing cycle to determine if there is any improvement with the defect distribution over time.
Defect Leakage
There can be serious consequences when flaws appear in the production process, so the Defect Leakage is a metric that can measure how well manual software testing and automation is being done, and how many problems are being overlooked during testing. Having an efficient bug removal approach and keeping track of issues found and fixed prior to release are characteristics of robust and effective software development.
Keeping track of bugs discovered after release and reporting them to DevOps is vital so issues are promptly fixed, test cases can be updated, and procedures can be reviewed. Transparency with software defects is just as important as identification and correction.
Defect Leakage = Number of defects in UAT / Number of defects found in QA Testing
Metrics in Agile
Software quality metrics in agile are touchstones that offer information about every stage in the software development lifecycle. Projects where no data is tracked makes it difficult to determine the value of quality assurance & testing. It is a reality that in some cases, metrics are negatively used to pit teams against each other or for individual criticism. Unsurprisingly, this may create an ambivalence towards using QA metrics.
However, good Agile metrics that are tracked and communicated help clear up confusion and provide clarification on the team’s strengths and weaknesses throughout the development cycle. Staying on course requires gathering and evaluating pertinent data and leveraging the connection with KPIs to drive quality, raise standards, and improve teamwork with the primary objective of producing top-class applications.
To Sum Up
Lack of knowledge in building a proper QA process results in unstable releases, missing deadlines, and issues accumulating with every release. Metrics are not a panacea, but they are an essential element of effective planning of the QA and, as a result, the development activities.
Metrics are important regardless of the methodology you’re using. Some believe that Agile doesn’t rely on any documentation or tracking. However, it is not true: Agile only minimizes the number of documents and requirements to those that help shape a better process and, thus, achieve better product quality.
