The benefits of QA testing in software are widely accepted. However, quantifying these benefits and optimizing the performance is tricky. The performance of software development can be measured by the difficulty and amount of code committed in a given sprint. Measuring the effectiveness of QA is harder when its success is measured by the lack of problems in software application deployment to production.
If you can’t measure it, you can’t improve it.
The ‘right’ metrics to evaluate QA effectiveness depend on your organization. However, it is generally a good idea to measure efficiency and performance for a well-rounded guide for performance evaluations.
While improving test coverage ideally means creating more tests and running them more frequently, this isn’t the actual goal, per se. It will just mean more work if the right things are not getting tested with the right kind of test. Hence the total number of tests in your test suite by itself isn’t a good metric or reflection of your test coverage.
Instead, a good metric to consider would be to check if your testing efforts cover 100% of all critical user paths. The focus should be on building and maintaining tests to cover the most critical user flows of your applications. You can check your analytics platform like Google Analytics or Amplitude to prioritize your test coverage.
The perfect test suite would have the correct correlation between failed tests and the number of defects identified. A failed test will always include a real bug and the tests would only pass when the software is free of these bugs.
The reliability of your test suite can be measured by comparing your results with these standards. How often does your test fail due to problems with the test instead of actual bugs? Does your test suite have tests that pass sometimes and fail at other times for no identifiable reason?
Keeping track of why the tests fail over time, whether due to poorly-written tests, failures in the test environment, or something else, will help you identify the areas to improve.
Time to test
The time taken to test is a crucial indicator of how quickly your QA team creates and runs tests for the new features without affecting their quality. The tools that you use are a key factor here. This is where automated testing gains importance.
Scope of automation
Automated testing is faster than manual testing. So one of the critical factors to measure your QA effectiveness would include the scope of automation in your test cycles. What portion of your test cycle can be profitably automated, and how will it impact the time to run a test? How many tests can you run in parallel, and the number of features that can be tested simultaneously to save time?
Time to fix
This includes the time taken to figure out whether a test failure represents a real bug or if the problem is with the test. It also includes the time taken to fix the bug or the test. It is ideal to track each of these metrics separately so that you know which area takes the most time.
Tracking the number of bugs found after production release is one of the best metrics for evaluating your QA program. If customers aren’t reporting bugs, it is a good indication that your QA efforts are working. When customers report bugs, it will help you identify ways to improve your testing.
If the bug is critical enough in the first two cases, the solution is to add a test or fix the existing test so your team can rely on it. For the third case, you may need to look at how your test is designed—and consider using a tool that more reliably catches those bugs.
Is your Vendor up to the mark?
Outsourcing QA has become the norm on account of its ability to address the scalability of testing initiatives and bring in a sharper focus on outcome-based engagements.
Periodic evaluation of your QA vendor is one of the first steps to ensuring a rewarding long-term outsourcing engagement. Here are vital factors that you need to consider.
Communication and people enablement
Clear and effective communication is an integral component of QA, more so when DevOps, Agile, and similar collaboration-heavy initiatives are pursued to achieve QA at scale. Ensure that there is effective communication right from the beginning of the sprint so that cross-functional teams are cognizant of the expectations from each of them and have their eye firmly fixed on the end goal of application release.
Also, your vendor’s ability to flex up/down to meet additional capacity needs is a vital factor for successful engagement. An assessment of the knowledge index of their team in terms of ability to learn your business and their ability to build fungibility (cross skill / multi-skill) into the team can help you evaluate their performance.
The right QA partner will be able to create a robust process and governing mechanism to track and manage all areas of quality and release readiness, visibility across all stages of the pipeline through reporting of essential KPIs, documentation for managing version control, resource management, and capacity planning.
Vendor effectiveness can also be measured by their ability to manage operations and demand inflow. For example, at times, toolset disparity between various stages and multiple teams driving parallel work streams creates numerous information silos leading to fragmented visibility at the product level. The right process would focus on integration aspects as well to bridge these gaps.
The intent of a QA process is mainly to bring down the defects between builds over the course of a project. Even though the total count of defects in a project may depend on different factors, measuring the rate of decline in the defects over time can help you understand how efficiently QA teams are addressing the defects.
The calculation can be done by plotting the number of defects for each build and measuring the slope of the resulting line. A critical exception is when a new feature is introduced. This may increase the number of defects found in the builds. These defects should steadily decrease over time until the build becomes stable
Measuring the time efficiency often boils down to the duration it takes to accomplish the task. While it takes a while to execute a test for the first time, subsequent executions will be much smoother and test times will reduce.
You can determine the efficiency of your QA team by measuring the average time it takes to execute each test in a given cycle. These times should decrease after initial testing and eventually plateau at a base level. QA teams can improve these numbers by looking at what tests can be run concurrently or automated.
Improve your QA effectiveness with Trigent
Trigent’s experienced and versatile Quality Assurance and the Testing team is a major contributor to the successful launch, upgrade, and maintenance of quality software used by millions around the globe. Our experienced responsible testing practices put process before convenience to delight stakeholders with an impressive industry rivaled Defect Escape Ratio or DER of 0.2.
Trigent is an early pioneer in IT outsourcing and offshore software development business. We enable organizations to adopt digital processes and customer engagement models to achieve outstanding results and end-user experience. We help clients achieve this through enterprise-wide digital transformation, modernization, and optimization of their IT environment. Our decades of experience, deep domain knowledge, and technology expertise deliver transformational solutions to ISVs, enterprises, and SMBs.
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