Only Need These 5 QA Metrics to Improve Software Testing

In this piece, we’ll keep things simple with five useful metrics for analyzing and enhancing QA, which are divided into two categories: test effectiveness metrics and test efficiency metrics.

• Escaped Bugs
• Test Coverage
• Test Reliability
• Time to Test 
• Time to Fix

QA Metrics for Assessing the Effectiveness of Tests

The purpose of software testing is to ensure that the programme you’re going to release fulfills your quality requirements. Passed tests should, in theory, indicate that the product is ready for release, while failed tests should suggest that the feature may require more attention before being released—but this isn’t always the case. That’s why we utilize QA metrics to assess how effectively our test results represent the software’s quality.

Escaped Bugs

Any bugs that make it to production after the testing cycle is complete are known as escaped bugs. Customers or team members frequently find and report these defects after a feature goes live.

If an issue got through, it’s most likely because your test suite overlooked it. This might occur for a variety of reasons:

• Your present test suite may not cover the user route in question.
• There may be a test for that user path, but it may be obsolete or unreliable; therefore, the team disregards failing findings.
• There is a test for that user route, but it is written in such a way that it passes even if certain errors occur.

If the problem is significant enough in the first two circumstances, the remedy is to add a test or repair an existing test such that your team can rely on it. In the third situation, you might want to reconsider your test strategy and options were considered a tool that can more reliably catch those errors.

Test Coverage

More testing implies more labor if you’re not testing the correct things with the proper sort of test. You may have a test suite of 500 thorough tests and yet have less effective test coverage than someone who just has 50 tests to cover the most important elements of their product. As a result, the overall number of tests in your test suite does not accurately reflect your test coverage.

Rather than attempting to cover 100% of your application, we propose focusing your testing efforts on 100% coverage of all essential user pathways. In this post, we go into further depth on how to determine the most vital channels, but the short version is to think of a snow plowing the streets of a city after a snowfall. The streets with the greatest traffic are cleared first, while some side streets may never see the light of day.

Test Reliability

The amount of defects and failed tests in an ideal test suite would be perfectly correlated. A failed test would always include a true issue, and tests would only pass if the product was completely devoid of bugs.

Comparing your findings to this criterion is one way to assess the dependability of your test suite. How often do your tests fail due to test-related issues rather than actual bugs? Do you have tests that pass part of the time but fail others for no apparent reason?

Tracking why tests fail over time—whether it’s due to bad test writing, test environment issues, or anything else—will help you spot patterns and pinpoint where you can improve.

Time to Test

The metric “time to test” measures how quickly your team can write and execute tests for new features without compromising quality.

The software testing tool you employ will have a significant impact on ‘time to test.’ Manual testing is substantially slower than automated testing.

Time to Create Tests

Creating automated tests using a no-code tool like Rainforest QA is faster than writing out lines of code for each action and assertion—even if you have programming experience. Autobotzit QA also lets non-technical team members create and maintain tests without learning a new programming language just for testing. That means anyone can help create speedy automated tests while developers focus on building features.

Time to Run Tests

Many development teams use time to test as a measure without considering other considerations (e.g., “these tests take an hour, let’s reduce it down to 30 minutes”). Looking to finding inefficiencies is a better way to approach the time it takes to test. This will guarantee that you aren’t sacrificing quality in order to speed up the release process.

Time to fix

The time it takes to discover whether a test failure is due to an actual bug or a fault with the test, as well as the time it takes to correct the defect or the test, is included in the ‘time to fix’. It’s advisable to keep track of each of these metrics separately, so you can see which one takes the longest.

Autobotzit includes video replays of every test run to assist you in determining why a test failed (whether it passes or fails). You can see the actual point of failure as well as everything that led up to (and after) it in these videos.