Quality Assurance is vital today. It ensures that the end product is reliable and efficiently meets the requirements of the customer. The quality can be assured in a more absolute sense when there are certain tests run on it every now and then, and measured as well. This measurement comes through Quality Assurance Metrics.

Quality Assurance metrics are a set of tools and techniques to measure and improve the quality of software products. They are used to help in reducing the number of bugs, issues and make QA measurable.

There are many software testing metrics that can be used to measure the quality of software. However, the following top the charts:

– Code coverage

– Defect density

– Defect removal efficiency

– Defect prevention efficiency

– Regression testing

These QA metrics fall into two categories: process-oriented and outcome-oriented metrics.

Process-oriented quality assurance metrics are related to the processes used in software testing, while outcome-oriented quality assurance metrics are related to the result of software testing.

Let’s look into these metrics closely;

Code coverage: Measures how much code has been tested by a test suite or automated tests. It’s a very useful metric that can help you assess the quality of your test suite, and the experts will see here how you can get started with your projects. It tests your code several times before giving the final result.

Software testing is a crucial process in software development. The quality of the product depends on it.

Defect density: Defect density is numerical data that determines the number of defects detected in software or components during a specific development period. It is then divided by the size of the software. In short, it is used to measures how many defects exist in relation to lines of code.

Quality assurance metrics are essential to software testing. They help us measure the quality of our software and the effectiveness of our testing process.

Defect removal efficiency: Also known as DRE is the most important measure of testing. It  allows the development team to eliminate bugs prior to its release. It measures how many defects were found during testing, fixed, and verified by a second person before being released to production.

DRE is calculated as the correlation of bugs detected internally with the number of bugs that were detected externally.

Defect prevention efficiency: Measures how many defects were prevented by design, coding standards, static analysis, or other means before reaching production. This QA process involves a structured problem-solving methodology to identify, analyse and prevent the occurrence of defects. This metric ensures that defects that are being detected so far, should not appear or occur again.

Defect prevention is a key activity in the software development process. Late defect detection adds massively to costs.

Regression testing: It is a software testing practice that ensures an application still functions as expected after any code changes, updates, or improvements. It is a type of testing which confirms that any recent program or change in code has not adversely affected the existing functionalities.

Regression testing is responsible for the overall stability and functionality of the existing features.

A Note to Testers

Testers use these metrics to measure how well they are doing their job, what areas need more attention, and which bugs they should prioritise fixing first. These metrics are not just limited to bug count and code coverage, but also include a variety of other aspects that can be measured.

Summing Up

All in all the quality assurance metrics are very useful for measuring the performance and efficiency of testing processes, identifying problems with the code, and determining how well testers are doing their job. They can also be helpful to analyse how well a company is testing the software as well as find out what needs to be improved in a company’s testing process andwhich area requires improvement.

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Written by Infiwave Solutions