What does success mean to you?
In both personal and professional lives, we have different ideas of success. Some want stability, and some are wanderers. For developers, success is producing clean and efficient code; for designers, success is creating visually appealing designs.
So, what is success for QA Engineers?
Many people claim that finding bugs is the primary purpose of QA, but when does it end? Because bugs will always be there! We can regularly find new bugs even in the most widely used apps.
So, if you evaluate QA success by the number of bugs found, we will never look successful.
In my experience as a QA engineer at Gurzu, I have figured out a broader vision of metrics for software testing. I will explain 7 of them in this blog.
What are metrics?
Metrics are the standard unit of measurement that quantifies the results. For businesses, the financial indicators can be their metrics. In healthcare, the treatment success rate can be a metric.
What are software metrics?
Similarly, Software metrics track and evaluate the performance, progress, and success of software processes, products, and services.
Testing metrics help us to determine what types of enhancements are required to create a defect-free, high-quality software product.
We use testing metrics to increase the overall productivity of the development process and to provide a quantitative approach to the development and validation of software process models.
The challenge with testing metrics is that the test objects that we want to measure have multiple properties that can be described in many ways:
For example, the number of bugs found in a test effort is not meaningful as a measure until I combine it with the severity, types of bugs found, number of bugs fixed, and so on. Now, with these multiple properties, I can make my clearest and most convincing arguments when I stick to fundamental metrics.
QAs are often asked many questions. Like:
- How long will it take to test it?
- How much of it has been tested?
- What about the bugs?
- How much of it has to be tested?
- How good were the tests? etc
Fundamental testing metrics are the one that can be used to answer these questions.
The first metric for today is Test Coverage.
1. Test Coverage
Test Coverage is an important metric because it helps to identify which features of the applications have been tested already and which are not. Untested modules or features can lead to bugs or issues when the software or application is being used.
Also, Test coverage helps to ensure that all the requirements or functionalities of the software or applications have been covered in the development and testing phases.
Not just that, we also document test coverage with reports like test case reports and test closure reports. These reports help in further regression testing. It reduces the time of regression testing and helps to identify bugs faster and quicker in the later phase.
This metric helps to measure the test effort itself, answering questions about how much was tested, what was achieved, and how productive the test was.
Test coverage measures the percentage of code or requirements that have been tested.
For example, if the test suites cover 80% of functional requirements, it indicates that 20 % of requirements are not tested. These metrics help to identify areas that may need additional testing.Another metric is Test Execution Time.
2. Test Execution Time
Simply put, it is the time it takes to execute a set of tests.
It is essential because it shows the efficiency of your testing efforts.
My QA team at Gurzu once optimized a regression testing that used to take 4 hours to run to be completed in only 2 hours. The time we saved here might not look like a lot, but the sum of all the time we saved eventually meant that the feedback loop was quicker.
Ultimately, it accelerated the development cycle, and software updates were deployed promptly. It is small things like this that meet customers’ expectations, and we gain their trust.
So, in an agile and fast-paced development environment like ours, shorter test execution time is a handy metric.
The third metric is Defect Density.
3. Defect Density
Defect density is the number of defects or bugs present in software per unit of code. It is often expressed as defects per thousand lines of code. So, if you divide the number of bugs found per thousand lines of code, you have your defect density!
This metric is convenient when you are about to release a module, so defect density can help you recognize its readiness for release.
When your defect density is low, it can suggest higher reliability. So, this is also a way of measuring the effectiveness of your testing efforts.
Number four on the list is Severity and Priority Distribution.
4. Severity and Priority Distribution:
It refers to the categorization of defects based on severity and priority. Severity here means the impact of a defect on the system. It can range from critical to minor. Similarly, priority is the order in which the issue should be addressed. Priority can go from High to low.
For example, if a critical functionality defect is identified, it needs immediate attention. Other medium- or low-priority issues can be addressed in the next release. This helps in effective defect management.
Similarly, the fifth metric is the Test pass rate:
5. Test Pass Rate
It refers to the percentage of test cases that pass successfully out of the total number of test cases executed. For example, if a test suite consists of 100 test cases and 80 of them pass, the test pass rate is 80%.
Why is this metric important? It provides a quick indication of the overall quality of the software.
By measuring the test pass rate, we can identify the potential issues early on and take corrective actions to ensure the stability of the testing process. Because if you have a really low test pass rate, you know there’s something wrong with your software.
This metric also comes in handy to decide whether the product is ready for deployment or if further refinements are needed.
Another metric is Requirement Traceability:
6. Requirement Traceability
It is the process of mapping test cases to the specific requirements they cover.
For example, if a requirement states that “a user should be able to reset the password,” there should be corresponding test cases to validate this functionality.
Requirement traceability is essential to verify that all the requirements are tested and that there are no gaps in coverage.
It serves various purposes. Firstly, it helps ensure the developed software aligns with the intended specifications. Secondly, it is helpful in risk management by allowing us to identify any untested requirements.
Lastly, it is valuable in change management, as it provides insight into the impact of any alterations to the requirements on the testing process.
So, overall, requirement traceability ensures that the final product meets the intended objectives and provides a structured approach to managing changes throughout the software development lifecycle.The last metric that I want to talk about is test effectiveness.
7. Test Effectiveness
Generally speaking, it isn’t easy to measure things like effectiveness. We QAs measure test effectiveness based on the ability of our testing process to identify and address the critical issue.
For example, if a test suite is designed to find defects and successfully finds critical issues, the testing strategy is effective.
Conclusion
I want to conclude this by saying that time, test, bugs found, etc, are all the fundamental metrics of software testing. When these metrics are taken together, they can provide a valuable and complete set of information that helps determine the success of QA
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