QA Metrics Every Tester Should Consider

Despite having the best test management tools at their disposal, QA engineers are often struggle to produce satisfactory test cases. They often let go significant bugs which negatively impact user experience after launch. Using the right QA metrics is just as important as using the best Test Management Tool. So, here are 9 QA metrics every tester should consider during QA activities:

Defects Per Software Update

When a new feature is added, it often introduces bugs or defects that didn’t exist in the previously conducted tests. For example, if you add a new button, tests might show that other buttons that were added previously have started having misaligned tests and are having issues. These bugs are a result of an update. For example, after 5 updates, if the developers find 30 bugs in the software, they’ll assume that 6 bugs are attributed to every update. However, it is possible that one update might’ve caused more than 6 bugs.

Study QA Matrix

By studying this QA metric properly, you’ll be able to make more informed and accurate projections about what and how many bugs you can expect with a software update. This can help your team plan resources, availability, time, and overall investment.

Bugs Found vs. Bugs Fixed

A QA process’s success and overall efficacy depend heavily on the ratio between the number of bugs found and the number of bugs fixed. This test metric helps QA engineers find out the pattern in which the bugs are showing up and getting removed. This shows how well the defect management process is going. To find this ratio, a tester must track the number of bugs found and resolved in every test cycle. Based on the results of different test cycles, the tester can determine whether the results are getting more accurate or not.

Test Case Productivity

Not many QA teams consider this testing metric important. However, by measuring test case productivity, you can set realistic goals and objectives for your team. This metric measures your team’s effort to build test cases for a specific cycle. Here’s the formula for calculating test case productivity:

Test Case Prod. = (Number of Test Cases/Effort required per Test Case) x 100

Remember, this is just an estimate, as the effort required per test case can’t be an exact number. However, this metric can provide your team with a sense of what is practically achievable per cycle.

Test Review Efficiency

Test cases may have flagged bugs. Still, a tester must review every flag, whether it takes a few minutes or hours. Sometimes, the tests can return many bugs depending on the software and its development stage. The reviewing time adds up. Hence, calculating test review efficiency becomes important. Here’s the formula for calculating test review efficiency:

Efficiency % = (Number of tests reviewed/ Total number of tests remaining) x 100

For example, let’s say during a 7-day-long testing process, a QA team managed to detect 65 bugs. But, considering the nature of these bugs, they could only review and forward 50 of them. Therefore, the test review efficiency will be around 79%. This is a good way to measure your team’s performance.

Defect Leakage

In this metric, a tester has to monitor the number of bugs that escaped to the user acceptance testing (UAT) stage. It refers to the number of bugs in the UAT after the software or app has undergone multiple testing rounds. It’s recommended to take care of this metric before your digital product launches. Here’s how you can calculate defect leakage:

Defect Leakage = (Total numbers of defects in UAT/ Total number of defects found prior to UAT) x 100

Defect Age

Defect age is a metric that measures the time developers take to fix a bug or defect from the time when the bug was discovered or created. Here’s the formula for calculating defect age:

Defect Age = Difference between the time of bug creation and time of bug revision

Defect age is usually calculated in days. For example, if a bug was created on 11/12/2021 and was fixed on 29/12/2021, the defect age of the bug is 18 days. Lower defect age indicates the efficiency and maturity of your QA processes.

Cost Per Bug Fix

Defect age measures a developer’s time while fixing a bug. Similarly, cost per bug fix is a metric that’s used for calculating the amount spent by the QA or DevOps team on the detection and fixation of each bug. Here’s how to calculate the cost per bug fix:

Cost per bug fix = time taken to fix * the dev’s hourly rate

You can also calculate the cost of testing each bug fix for better final reporting.

Test Reliability

Measuring the reliability and success of tests is important for every QA procedure. This test metric has the following characteristics:

• Close correlation between failed tests and number of bugs
• Each failed test contains a real bug
• A test will only pass when the feature under assessment is bug-free

If your test meets or comes close to these benchmarks, then it’s reliable. Tracking reliability is necessary to check whether or not QA is doing a great job. This also helps QA engineers continuously improve on their practices, scenarios, and test cases.

Escaped Bugs

Avoid confusing this testing metric with defect leakage. The number of escaped bugs determine the progress of your entire QA process. The purpose of this metric is to ensure that customers don’t detect any defect or bug in the app or software after launch. If your customer isn’t reporting any bugs while using your digital product and your QA and dev team isn’t pausing everything to fix bugs, then your QA procedures are producing great results. However, if bugs are repeatedly escaping and affecting user experience, then you might have to reconsider your test suites.

Conclusion

Apart from having sufficient knowledge regarding important QA metrics, a tester should also use the best Jira test management tool which allows them to create accurate and effective test cases. Using the right Jira test management tool is crucial for rolling out bug-free software and apps.