Businesses face numerous challenges while ensuring the accuracy of software products, especially in today’s fast-paced digital world. This is where AI automating testing comes in! With the power of AI, you can revolutionize your testing process and overcome all the challenges of traditional methods.
What are the challenges with traditional test automation?
Objection recognition:
Identifying the objects correctly is a crucial element in automating the tests. Traditional test automation tools use specific attributes such as IDs, XPath, names, classes, CSS selectors, etc, to identify objects.
The automation scripts imitate the user actions such as typing text into fields, clicking the buttons, checking the displayed information, selecting options from drop-down menus, and many more after identifying the objects.
When the attributes are changed, the objects in the traditional test automation tool are not recognized. As a result, the test script is then unreliable. Identifying and updating these objects in the repository takes a lot of time and effort annually. This can greatly slow down the testing process, which makes it more difficult.
Appropriate size of the regression test suite:
Which aspect to test and which one to omit is one of the aspects that most companies struggle with. As the quality assurance experts depend on their expertise to choose the regression test cases, this can be costly.
Unfortunately, such choices are based on assumptions that result in multiple tests that are time-consuming or too few, which pose risks for the business. Therefore, it is crucial to understand the factors that must be considered when choosing the regression test scenarios to avoid such issues.
Plan and design the workload for performance testing:
It can be challenging for load testing to create a workload that accurately reflects the application’s actual usage. This is because it consists of understanding the peak traffic times and usage patterns. Making multiple users act concurrently is another issue in simulating user behavior. So, it is very crucial to properly design and plan the workload for performing the test to get accurate results.
Test data management:
When the business uses testing applications such as SAP, Oracle, Workday, and Dynamics 365, this test data management is crucial. To mimic real-life situations, testers need data and experiences that users will have. The critical problem may be overlooked if they do not have the correct and relevant test data.
Conclusion
To wrap it up, businesses and technical users can now easily automate their application testing in just a few hours with the help of Opkey, a no-code test automation platform, without coding. Opkey supports over 15 packaged apps and 150 technologies that can automate single-app and cross-app tests without problems. Opkey also speeds up the test cycle eight times with 30,000 pre-built and automated test components. This helps reduce the test maintenance efforts by 80%. Opkey is the fastest testing automation platform in the industry, and it uses automated script technology and a cross-browser interface.
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