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"You can't improve what you don't measure" - this saying is rightfully true for the world of software quality assurance. Quality Assurance (QA) metrics are used to estimate the progress and outcome of test results. Through metrics, it is easy to track the status of QA activities, measure team efficiency, and optimize processes.

These are indicators that can quantitatively help to evaluate the quality and efficiency of the software development and testing life cycle. Without these metrics , software quality cannot be measured, explained, or demonstrated in any meaningful way.

Several critical metrics must be defined and monitored during the development process to determine how well a product performs. Let us take a deep dive into those metrics in this blog post.

What Can QA Test Metrics Track?

Quality management metrics in software testing allow us to keep tabs on the state of QA operations, assess team effectiveness and product quality, and make improvements to our workflows. Team leaders can utilize QA testing data to determine the productivity of a team over time and prepare for the future. For example:

• You can estimate the amount of time needed for regression by keeping track of the number of tests introduced to a new version of the software.
• The amount of bugs found is a good indicator of how much testing the team will have to do after the developers have fixed the defects.
• Teams can better assess the efficacy of their strategy and testing methodologies by using software testing metrics. As a result, they will be better equipped for each new cycle of releases.
• QA metrics shed light on the general behavior of software programs. Because of this, QA engineers will be able to identify and fix similar product defects much more quickly.

However, remember that metrics and measurements in software testing are merely numbers when taken out of context. To accurately evaluate a team's performance, you must consider the project's specs, the estimated delivery date, the company's workflows, and so on.

The Fundamental QA Metrics

There are two kinds of QA metrics to track: absolute and derivative. Test results and product quality can be assessed by either of these methods. Let's look at various quality assurance metrics examples and how they can be gathered or computed.

Absolute Metrics

Absolute metrics are based on data obtained during the development and execution of test cases and tracked throughout the software testing life cycle. These software testing metrics indicate how well the testing process is progressing or how close it is to completion at a given point in time. These data are often called measurements since they contain information that can be counted. Some absolute metrics include:

• Total number of test cases
• Number of passed/failed/blocked test cases
• Number of identified/accepted/rejected/deferred bugs
• Number of determined/actual test hours
• Number of bugs detected after release

Derivative Metrics

More often than not, absolute metrics aren't enough to gauge how well the QA process is working. For instance, measuring the total number of test cases may not be sufficient to determine whether we are on track for completion or what outcomes we should evaluate each day. Because of this, it's difficult to assess how much effort testers put in each day to achieve one specific goal for quality assurance.

Here, the use of derivative software testing metrics comes into play. To calculate derivative metrics, you need to apply specific formulas to absolute measurements. This information is helpful for team leaders, test managers, and other stakeholders. Here are some of the common derivative metrics used in QA testing.

• Test Tracking

  The percentage of tests that pass, fail, or are blocked can be used to assess the quantity of testing that has been completed or is still to be completed. It also makes it easier to identify the areas that require the most attention at the moment. These metrics aid in ensuring that all testing tasks are completed efficiently.

  The following are some quality control metrics examples for test tracking:

  • Passed test cases coverage: This calculates the proportion of test cases that pass.
  • Fixed defects percentage: This metric allows the team to calculate the proportion of defects that have been fixed.
  • Average time taken to rectify defects: This metric allows the developers and testers to see how long it takes to fix a bug on average.

• Test Effort

  These metrics provide a comparison between what was anticipated before the testing process began and the actual effort put out by the testing team. Using this information can help you estimate future projects comparable to the one you're currently working on.

  Here are a few examples of test effort metrics:

  • Number of tests in a specific period: This counts how many tests were run in a particular time frame.
  • Test design efficiency: This metric is used to assess the test's design efficiency.
  • Bug find rate: This metric indicates how many bugs or defects the team discovered during testing.

• Test Effectiveness

  The test effectiveness metric monitors and analyzes a test set's capacity to find and fix bugs and defects. This metric is the percentage of defects found by a particular test compared to the total number of defects detected after release.

• Test Coverage

  This metric indicates the extent of the software testing and the progress of requirements. The test cases by requirements, the number of requirements covered, and defects per requirement are examples of this metric. It is a metric for determining whether testing activities have been completed and can be used as a criterion to conclude testing.

• Test Economics Metrics

  The cost of testing a website or app is influenced by several factors, including the number of people participating, tools, resources, and infrastructure. As a result, the testing team must compare the projected cost of testing with the actual cost. This can be done by looking at the following metrics:

  • Total projected costs of testing
  • Actual costs of testing
  • Variances from the budget estimate
  • Variances from the schedule
  • Average cost of a bug fix

• Test Team Metrics

  These metrics are helpful in determining how much work each member of the team is assigned and whether they require clarification or can take on more responsibilities. With these metrics, team members are encouraged to share project information without blaming anyone for any problems that have emerged. Test team metrics include:

  • Distribution of defects returned per team member
  • Distribution of open defects for retest per test team member
  • Test cases allocated per test team member
  • Test cases executed per test team member

• Test Execution

  This metric gives us an overview of how many tests have been run and are still pending. This can help evaluate the extent to which the test is covered during testing.

• Test Execution/Defect Find Rate Tracking

  This metric represents the percentage of tests that fail compared to the total number of tests run. There will be an early warning sign that testing processes need to be changed to meet targets when comparing the cumulative number of defects and test execution rates.

KPI for QA Teams

Several factors may be used to evaluate the efforts of a testing team, including determining whether capabilities match the requirements, whether deadlines are met, or the capacity to guarantee the absence of critical defects during production. However, particular KPIs for software testing teams can be used to gain more detailed reports on their performance. Using these indicators, you can make better decisions about the team's progress and optimize the overall workflow.

• Total number of tests executed: The number of tests performed by a team over a given period or throughout a specific project can be valuable, even if it doesn't necessarily correlate directly with effectiveness.
• Defect summary: This shows the number of bugs detected by a QA team during a particular timeframe, as well as the nature of the bugs.
• Defect removal efficiency: With this metric, the team's ability to identify software defects is measured.
• Number of covered requirements: This KPI is more illuminating in measuring efficiency because it reveals whether the testing process covers the entire product.
• Quantity of new, closed, and reopened defects: This metric changes based on project complexity; therefore, consider the time spent finding bugs and the rate with which bugs are reopened.
• Number of critical defects: This measure demonstrates the importance of testing. You can see how much you could lose if you don't do the testing by looking through the list of critical bugs.
• Automation coverage: This helps keep track of the automated test suite's relevancy so testers can devise a better approach for completing pending test cases.
• Automation velocity: Measures the number of test cases, the delivery of new scripts, and the allocation of resources to determine the automation rate during a particular time frame.

Conclusion

QA metrics and KPIs are enhancing the software testing process tremendously. These metrics are critical in the software development and testing life cycle since they help ensure the accuracy of the numerous tests run by your team and guarantee the product's quality. As a result, by adopting and implementing these QA metrics, you can improve the efficiency and reliability of your testing activities and get exceptionally high-quality results.

If you're looking for the appropriate QA metrics to use in your company, a dedicated software engineering and testing partner like QASource can help. Speak to a specialist today.