A software testing metric is a criterion to track the effectiveness of quality assurance efforts. First, you establish success indicators throughout the planning stage. Then, compare them with the received metric after the completion of the process.
However, many software QA and test experts tend to focus on how the tests will be executed rather than on the actual information produced by the tests. By this I mean testers often focus on the mere satisfaction of completing all the tests. But is this always a good thing? You can have a 100% pass rate with all green indicators on your dashboard and it is still possible that your tests aren’t strong enough.
This article will discuss five software testing metrics that might assist QA professionals in evaluating their success.
Characteristics of a “Good” Testing Metric
Let’s talk about the features a metric should ideally have.
Relevant to Business Goals
Critical KPIs should reflect the primary mission and purpose of a business; for example, monthly revenue growth or the number of new users. Each company chooses its metrics based on what they intend to achieve with their product. While it may seem attractive to succeed in all tests, focusing on the wrong goals can be deceiving. This may impact the app’s work and the entire complex system, such as headless commerce architecture.
Allows for Growth
Every metric should allow for improvement. What if you’ve achieved a 100% success rate? The goal may be to keep the metric at this level or to improve it further.
Encourages Development of a Strategy
When a metric gives a team a goal, it also motivates them to ask questions to develop a plan. Suppose you need to increase revenue. Consider whether the product requires new features to encourage more purchases. Is it necessary to create a new acquisition channel? Has the competitor launched any new products or features that are attracting new buyers?
Trackable and Comprehensible
Good metrics are simple to comprehend and follow. Otherwise, how will the people gathering them make informed decisions? Employees must understand what they can do to improve the outcome.
Three Tips for Choosing and Measuring Software Testing Metrics
1. Start by Asking Questions
Your questions should cover three topics:
1. What you’re measuring
2. Strategies and tools to measure it
3. Reasons to track it
To avoid analyzing useless metrics, pay attention to the metrics definition process. Sometimes, a small number of backlog bugs means your QA team is doing its job. However, when you break down these bugs into high/medium/low priority issues, you’ll be able to better see the overall program quality and make the needed adjustments.
2. Don’t Neglect Automation When Calculating QA Metrics
Automation saves you time on manual data collection and helps ensure your metrics will always be relevant. Let’s assume you use Jira. Set up a Jira Query Language (JQL) request on your Confluence page if you need data on critical bugs every sprint. It will be updated frequently. Or you can employ other tools based on your preferred test management/task tracking system.
3. Collect Comments and Gradually Improve Metrics
Once you’ve set up and gathered all the metrics, the feedback and improvement processes start. Pay attention to feedback to improve the efficiency and clarity of your metrics and reports.
Five Software Testing Metrics to Track
Now let’s look at some specific examples. Note that different quality aspects matter to varying degrees depending on circumstances.
1. User Satisfaction
Here, you’ll want to see the client’s reaction to the product. You use user satisfaction surveys and support tickets that reveal bugs. If you track these quality metrics and work to improve them, the business will grow as you’ll see more satisfied and returning customers. If something’s wrong, you’ll have to do a causal problem analysis and remove the roadblocks.
2. Process Metrics
These are internal measurements that have a significant impact on your product quality. For example, you can track lead time and the time it takes between setting the task and code deployment and production.
One more metric you could use is cycle time. It means time to build a feature after being given the approval to begin working on it. Finally, you can track the time it takes to solve difficulties. This could refer to the speed of resolving tickets or bugs once they’ve been reported.
As these metrics can be hard to measure, another method to improve process efficiency is to detect where unfinished work starts to pile up in the queue. It can highlight a bottleneck that, if removed, could help your teams become more productive.
3. Coverage Metrics
Another indicator of test quality is test coverage. It informs us of the amount of tested code. It’s a method of ensuring that your tests check the code and how much they operate. In this case, it’s better to use a top-down strategy. The first step is analyzing module coverage. Then you consider functionality and, finally, data coverage in each functionality. It means how many different combinations of the potential data inputs you’re covering with tests.
This group includes such metrics as:
â—Ź Requirements coverage percentage
â—Ź Unit test coverage
â—Ź Manual or exploratory test coverage
â—Ź Test cases by requirement category
â—Ź UI test coverage
â—Ź Integration and API test coverage
4. Code Quality Metrics
Evaluating code quality means categorizing the value of code into two categories: Good and bad. There is no single notion of quality because practically every developer defines for themselves what constitutes good code. How can you assess code quality? Tools like SonarQube let you reveal how much technical debt is in a system. You’ll need to classify issues and vulnerabilities, organize them by priority and select what you’re going to focus on.
5. Bug or Incident Metrics
Each issue differs in severity, so don’t give all issues equal weight. Some problems are simply suggestions for improvement. Determine which components of quality are more important than others for your company. That said, go beyond just the amount of defects when analyzing the metrics you’ll use.
What can you extract from incident reports? These results can include:
â—Ź Total number of bugs
â—Ź Open defects
â—Ź Closed defects
â—Ź The time to close each incident report
â—Ź Changes since the last release
Rules for Measuring Software Testing Metrics
Evaluating metrics in software testing and estimating their success can be frustrating and vague. Here are some tips and suggestions you can use:
1. Correlate your metrics with project, process and product goals. Keep in mind that a single indicator is not enough for a complete view of your software quality.
2. Track the progress (or regress) throughout time. Streamline the data collection process through automation, store data in a collaborative resource like a Wiki/Confluence and review outcomes regularly.
3. Report the statistics to the customer and the team to show your progress. Reports should be easy to understand, so make them helpful and user-friendly.
4. Check to make sure if the metrics are valid. Keeping track of irrelevant metrics and displaying inaccurate data is out of the question.
Measurement is an important activity in software testing, such as determining the number of successful tests against how many have failed. All the information you get comes to stakeholders. As a result, they can make informed decisions such as when to release an app.
How can you monitor your test activities? You need to determine relevant software testing metrics. Choosing the correct testing metrics can be difficult. Frequently, teams opt for metrics that are out of sync with the overall business.
What can the lack of adequate benchmarks cause? Stakeholders fail to measure progress, identify possibilities for development or control which testing tactics have the most positive impact. All things considered, QA teams need to track individual progress, skill level, and success, as well as code quality, bugs, and coverage.
