QA & Testing Metrics That Matters Most for Success in 2024
Introduction
Did you know that even a minor bug can lead to significant revenue loss? But, it can be avoided by focusing on the right QA & testing metrics. Effective QA processes not only identify and rectify bugs but also streamline the development lifecycles, minimise costs, and enhance customer satisfaction.
But how do you measure the effectiveness of your QA efforts?
Here at Robotico Digital, with our expertise in Quality Assurance Solutions, we understand the importance of measuring success through the right QA and testing metrics.
Right Approach to Testing and Improving QA
QA should be based on an effective testing strategy. This should include functional testing, non-functional testing & performance testing. A proper testing plan is all about achieving proper test coverage, reducing the probability of bugs going undetected, and making the testing phase as efficient as possible. Even stats show that with the right approach, QA & Software Testing is helping businesses improve service quality by 50%, transform business by 50% and most importantly reduce their cost by 71%.
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Here are some pointers for an effective testing strategy-
- Identify the right testing tools and techniques: Choose the best-suited testing tools and methods from the available ones depending on the needs of a certain project.
- Prioritise test cases: Start with the crucial and risky areas, which involve the primary activities of the business.
- Automate repetitive tasks: Use test automation frameworks to run regression tests and allow the QA team to focus more on other kinds of tests.
- Integrate QA into the development lifecycle: It is recommended to integrate QA activities at every stage of development starting from requirement gathering to deployment. This is known as a Shift Left approach and can help identify and fix bugs earlier in the development process, reducing the overall cost of fixing them.
The Difference Between QA and QC in Software Testing
While both QA and Quality Control (QC) are instrumental in guaranteeing software quality, there’s a subtle distinction between the two.
| QA (Quality Assurance) | QC (Quality Control) |
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Top 10 Key QA & Testing Metrics for 2024
Now, let’s jump into the top trending metrics that will provide valuable insights into your QA and testing efforts:
1. Test Case Pass Rate:
This metric measures the percentage of automated test cases that pass successfully during each test run. While a high pass rate indicates a well-functioning system, aim for a balance. Low pass rates might suggest insufficient testing, while excessively high rates could point to outdated test cases that aren’t catching new issues.
2. Defect Leakage Rate:
Tracks the number of defects discovered in production environments compared to the total number identified during testing. A low leakage rate signifies a strong testing process that effectively catches bugs before release.
3. Defect Escape Rate:
Measures the number of critical defects that reach production despite testing efforts. Focus on minimising this rate to ensure a seamless user experience and minimise post-release fixes.
4. Test Automation Coverage:
Represents the percentage of functionalities covered by automated test scripts. A high automation coverage rate increases efficiency and consistency, allowing you to test more comprehensively.
5. Mean Time to Detect (MTTD):
It is used in Tracking the average time taken to detect the defect once it is integrated into the system. A low MTTD means that the tests are aggressive and the bugs that are caught are found early. Even BigPanda.io says that “lower MTTD means you’re discovering and solving problems quickly”. You can determine MTTD mathematically using this formula:
MTTD = (sum of incident detection times) ÷ (# of incidents)
6. Mean Time to Repair (MTTR):
MTTR Measures the average time taken to fix a detected defect. Optimising workflows and prioritising critical issues can lead to a faster MTTR and reduce the time users are impacted by bugs. An organisation can gain a lot of Other Benefits by simply measuring its MTTR count. You can also determine MTTR mathematically using this formula:
MTTR = (Total Resolution Time / Number of Solved Tickets)
7. Code Coverage:
Provides the assessment of the percentage of code coverage in the automated testing process. Although, a high code coverage percentage may not necessarily mean that all tests have been run, it means that a large part of your code is being tested and therefore, the chances of having logic errors are minimal.
8. Defect Resolution Rate:
Assesses the proportion of the identified defects that are effectively closed within a given period of time. A high defect-resolution rate shows the effectiveness of the team in handling problems and the ability of such problems not to slow down development.
9. Test Execution Time:
Record the time it takes to run through the whole of your test suite. Optimization of the test scripts and automation process means that the time taken to run the tests will be shorter, hence, the ability to test more frequently.
10. User Satisfaction
As for the last, it is not quite a technical factor, yet user satisfaction is the goal of good QA. It is advisable to carry out user polls or experiments to determine the attitude of users to the functionality, convenience, and satisfaction with the delivered product.
