Understanding Testability and Its Complexity in Upcoming Technologies
Testing is an important stage of the software development lifecycle. The purpose is to release bug-free, performant software that won’t require a fortune in backend running costs. Simply, making this process more effective and efficient will save you time and effort, and in the long run, will enhance your profitability. This is one of the major drivers behind the switch to test automation. Nevertheless, one crucial factor is often ignored– software testability.
You might naively think all software is equally simple or hard to test. But you only have to look at how developers write unit tests to understand this isn’t so. Without proper hooks for testing, many functions can only be tested completely by calling them from somewhere else and examining the results. Such functions are not very testable. But a well-designed function will involve its own unit tests. These enable you to check for certain that the function is working perfectly. In effect, this is making the function testable.
Further up the testing hierarchy, things become less obvious. Here, testability is about two things. Firstly, can you truly test the software, and secondly, how likely is it that your tests will expose any bugs.
For functional UI testing, there are various real difficulties for both manual and automated tests. Let’s look at these in more detail before then exploring methods you can build your overall application more testable.
Challenges posed to Automated Testing
Challenges of Manual Testing
Automation testing can never fully take over manual testing. One of the main advantages that manual testers have is that they are humans and extra intelligent than computers. This implies that the challenges they face are distinct from those acted by test automation. A major problem in manual testing could be the application state. A real-user can create up a complicated application state which indicates that replicating with manual tests can be time-consuming and daunting. Further, repeating the same tests is yet more challenging.
Common Problem in Manual & Automated Testing
Test data – a common issue that arises in both manual and automated testing. If testers are working to test a system, they require proper test data. They might just utilize their real customer data. But if your application deals with delicate data, let’s say banking data, QA teams cannot simply be permitted to access this data. On the other hand, if you have a new system there won’t be any test data though. In both conditions, you will have to generate fake test data. Although it sounds simple, it comes with a number of issues too.
How to Improve Testability
Improving software testability is more about updating code. This includes things like adding more specific unit tests, using tools to estimate test coverage, code reviews, etc. At the integration test level, it is important to know how each subsystem should function and may also need building code to test for this. The following are some ways to enhance testability:
- Make UI More Testable: Let’s explore what you can do to create your UI more testable.
- Better Element Naming: Software developers can enhance testability if they ensure that they name each element in the UI accurately. This is a huge challenge in large projects where there are large teams including frontend engineers and when teams are creating UIs for various platforms.
- Adding Tools for Testers: Manual testing is easier if you create tools especially for this. For instance, testers should be provided with tools that make it easy to place the application into a recognized state.
- Actual Test Environment: Although it can be challenging, yet it can help accomplish precise results for both manual and automated testing if your test environment replicates the production environment. All you require to do is assure that the staging environment is as near to the actual as possible. This involves using the same versions of software, similar servers, etc.
- Consistent Design: Consistent design is the solution to assure a good user experience. However, if you manage to generate a consistent design, this can enhance your software testability. It makes the method much easier for testers. They can simply reuse the test modules and knowing how the UI works help in making it more testable.
- Using ML and AI for Data Generation: Additionally, in modern times, companies can also utilize machine learning (ML) and artificial intelligence (AI) to create data that does not replicate the original database. Testing teams can use data that does not negotiate the sensitive user information, yet can be effective in getting the tests more testable.
- Internal Logging: The detailed logging of the internal state can assist in manual testing. It makes it simpler for testers to examine what is going on through any test. It is clear that more logging will influence your application but it will get the backend API visible to the testers.
The most failed application is the one with the least testability. Enhancing software testability will help in enhancing the overall software development method. Test automation significantly promotes testability. Moreover, it is necessary to use realistic test data to accomplish practical results.
TestUnity experts will help you enhance software testability which in turn improves your overall software development lifecycle. We ensure to produce high-quality test data and to test on a copy of your production environment. Connect with our experts to improve software testability.