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What Are The Metrics To Follow In QA Software Testing?

In a layperson’s language, QA or quality assurance can be defined as mechanisms, techniques, and processes that ensure the highest possible ‘quality’ of an organization’s products and services. Quality assurance, or QA, aims to prevent glitches and defects from surfacing in the first place. Therefore, quality assurance or QA metrics for software testing can be understood as a group of performance indicators that measure the ‘quality’ of a software product. While managing the development of a new software program, it is a common necessity to organize everything effectively and evaluate the product’s stature and abilities before the ‘big release.’ 

It is in such a context that software QA metrics come to the rescue. They serve as vital tools that help the stakeholders understand and improve different dimensions of the software project. However, it is noteworthy to mention that QA metrics do not improve the development of their own accord. The manager co-opts the metrics to gauge a clearer picture of the production process. By tracking the metrics, it becomes possible to understand where the quality strategy of the software is succeeding, where it is falling short, and what steps can be taken for further improvement. In simple words, QA metrics can help the manager handle the following aspects of software development

  • Defect prediction
  • Discovering and resolving bugs
  • Increasing productivity and efficiency of the software program
  • Efficient organization of the development trajectory 

Read also:-What Impact eCommerce Artificial Intelligence will bring in 2023

Top Five QA Metrics for Software Testing Worth Following 

After a crisp overview of QA metrics in software testing, it is time to delve into the crux of the article and examine the top five QA indicators you might consider adapting at your agency.

1. Mean Time to Detect (MTTD)

The first metric in our list is the mean time to detect or MTTD. As the name suggests, the metric can help your organization get a grip on the average time it takes to ‘detect’ issues or glitches. The pertinent relevance of the metric is that the sooner you discover a bug or a problem in the software, the faster you can fix the problem. When you measure the approximate time to discover the mishaps, you take the crucial first step in saving time, resources, and efficiency. And as we all know, it is cheaper to fix a glitch when discovered earlier. Thus, during the software testing process, do not make the mistake of sleeping on MTTD.

2. Mean Time to Repair (MTTR)

The second metric in our list is the mean time to repair or MTTR. As the name suggests, MTTR is the average time your organization takes to repair a glitch or bug that culminates in a systems outage. The MTTR metric is pertinent because when systems are ‘down,’ the company is not making any money. You ensure a seamless workflow and smooth revenue by tracking the metric and keeping it as low as possible. To calculate MTTR, you can follow the simple steps below –

  • Find out the total amount of downtime for a stipulated period.
  • Calculate the number of incidents in the same time period.
  • Divide the total downtime within the specified period by the number of incidents. Viola, you have the MTTR metric ready. 

3. Escaped Bug

Escaped bugs are ‘bugs’ that make it to the production process after the complete testing cycle. Customers or team members usually catch and report these bugs after the software or a feature goes live. Tracking the number of bugs that propped up post-release to production is an exceptional QA metric for software testing. If customers are not reporting problems, it is a good sign that your QA efforts are working. However, if people are not reporting on glitches, the ‘escaped bug’ metric can help you recognize ways to improve QA testing.

4. Test Reliability

The penultimate QA metric in software testing is ‘test reliability.’ The metric may be known by alternate names such as test robustness or its antonym – test flakiness. However, in simple terms, test reliability refers to the proportion of test cases that are not offering valuable or even usable feedback because of being ‘unreliable.’ An unreliable test means a unit test that is not rigid or deterministic. Sometimes, it passes, and other times it fails seemingly arbitrarily. Such inconsistency decreases the confidence of the software developers and other professionals in the test suit, hampering the production process.

5. Test Coverage 

Test coverage is the fifth most feasible metric for organizations of scales and types. It is a comprehensive metric that measures the amount of testing performed on the software program. The metric helps the QA team identify areas of the application they missed during initial testing and write extra tests to increase coverage. The test coverage metric ensures defect prevention at the earlier stages of software development, culminating in a lower maintenance cost. To calculate test coverage, you can follow one of the two formulas mentioned below –

  • Test coverage (percent) = (total number of tests run/number of tests to be run) x 100
  • Test coverage (percent) = 100 times the ratio of the lines of code that are actually executed by the test cases that are already in place

So, there we have it, the top five quality assurance (QA) metrics in software testing that you might consider worth adopting.

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