Before releasing a software application or sending it into the production phase, how many times have you had to ask, and try to answer an important question: ‘Have you tested your software application enough?’ Probably a couple of times that you may have even counted it. There is no escape to this question as well as the necessity to answer it with some meaningful answers and try to analyze its impact on the current project. In order to answer this question, we need to look at test coverage and the underlying testing criteria.
So one of the biggest challenges of software testing is knowing when to stop and how much testing is enough. Is it practically possible to achieve 100% success in testing an application? Or should a QA team prioritize the key areas that are more likely to have issues? Or should QA managers allocate resources in more efficient ways throughout the application, or simply concentrate on the basic testing efforts on more critical modules of an application?
In this post, we shall try to answer these questions. It is necessary to understand what test coverage is about, and which techniques should be used to make the most of a testing approach. Let’s begin with the fundamentals and define test coverage. Moving forward, we will also go through a list of test coverage techniques and explain how they can add value to the overall testing strategy of a QA team.
What is Test Coverage?
Test coverage is a metric used to determine whether testers are testing everything they are supposed to test. It allows QA testers to check the quality of their testing processes. By finding areas that are not covered currently, test coverage can help testers in developing tests for those key areas and improve the quality of these testing suites.
We understand it takes a lot of time and effort to build test cases. With the help of test coverage, QA experts can count the functions and then deploy different tests. Let’s have a look at an example. Let’s say you are testing an electronic pencil, then your focus should see if it is writing and with what font or thickness. Whereas, other aspects of trying to look for how the user should be able to use it easily include test coverage by feature and it is supposed to check if it draws as it should. The GUI icon, design, and size of a pencil should fit all requests, only then QA testers can claim that their tests have 100% test coverage.
Test Coverage Techniques
Let’s have a look at the test coverage techniques QA testers can choose from:
One of the basic techniques is product coverage, which defines the coverage from the perspective of a certain product. It includes defining all areas of the product that a team has already tested. Let’s assume the application you are testing is a simple mobile application. It is the most basic requirement for product coverage to verify that the operations work as intended. But this is not enough and there are other factors that need to be tested too. How well does this mobile application’s user interface look? Is it user-friendly? Does it perform the basic operations as users expect it to work? How does the application respond when a user interacts with an app that is unexpected? Does it work perfectly fine? Or it crashes? All these questions address the basic requirements of a product.
This is another type of coverage that is critical for any QA team. Sometimes, an application may work really well, but it fails to meet the users’ requirements. In this case, the app is useless for users. Let’s say you are testing a financial app and it performs the basic functions efficiently, but users fail to ensure successful online transfers. This affects the image of the mobile app and users abandon it. So what went wrong? Well, the list of requirements was not considered when creating test plans and test scenarios.
The risk coverage technique refers to the assessment of the risks associated with an application and that they have been thoroughly tested. It consists of all the risks involved in an application and ensuring that they are covered by these tests.
AI-based Test Automation
As the name suggests, this technique involves AI in automation testing. It consists of AI-based automation tools that apply machine learning to learn with each execution and improve them. This way, testers end up with a stable testing suite that provides better test coverage and ensures improving it over time.
Making the Most of the Test Coverage Techniques
We know the importance of test automation in any modern software company. It has a high ROI and comes with numerous benefits for any QA team. It is not possible to opt for a sound testing strategy without facing many challenges. One of these challenges includes deciding what and how much to test.
We live in a modern technology age, where experts have identified techniques that QA testers can use to make the most of their tests, which are known as test coverage techniques. Test coverage techniques help QA track the quality of their tests and cover the most critical areas, if not done yet. They also help in deciding what to test based on risks, prioritize the most crucial ones, and the ones that allow QA managers to allocate their resources more efficiently. AI-based QA testing tools can enable self-correcting test cases, that use their knowledge from each execution and then ease the burden of test maintenance – in other words, improve testing efficiency.