Test automation helps increase development speed while reducing cost and effort. In this article, we will share how to automate testing to help keep a test automation initiative on the right track with key tips for test execution, design and maintenance for large enterprise applications.
Each test automation project has its own specific needs. The right tool can significantly reduce testing time and improve testing team efficiency. The wrong tool can introduce unneeded complexity.
Select a tool that supports all the needed devices, browsers, OS versions, mobile platforms, the required test automation level (UI, API, database tests), test types (functional, load, performance, localization), and recognition technology (native, image, text). With a single tool, the learning curve for delivering automation will be reduced significantly and the same scripts will be reused for different platforms.
Further, we recommend going through the following checklist with the preselected tool:
Many test automation engineers tend to store test data (input, output, validation values) along with automation code. This approach overloads code with multiple duplications when new tests are added. Also, it significantly complicates test code maintenance, especially if an application under test (AUT) undergoes frequent changes.
To solve these challenges, we recommend you to employ DDT (data-driven testing) practices and organize all test data into tables in a separate file (a database file, an Excel spreadsheet, etc.). The DDT approach reduces the time needed to create new tests and increase accuracy as test engineers can easily re-use the same test data across different tests and avoid errors due to improved test code and data visibility.
Test automation is usually associated with automated testing via UI. However, testing via UI is rather time-consuming. UI tests can only be created closer to the end of a software development project. In addition, UI is prone to frequent changes – even in the final stages.
We suggest prioritizing API testing in functional testing. APIs are available earlier in the development cycle and remain quite stable. Moreover, an API test can be run in a few seconds, while the GUI test execution takes 2 minutes.
Modern applications are required to run in various browsers, operating systems and devices. This may lead to bugs caused by rendering inconsistencies. Testing against different browsers, OS, and devices with classic test scripting (asserting specific CSS rules, selectors, HTML markup) means significant additional effort.
We prefer to eliminate visual inconsistencies using screenshot comparison tools. Compare screenshots with samples to verify that an exact screen or object appears as expected. We would particularly highlight AI-based tools for visual testing (Applitools is their most popular representative) since they can differentiate accepted variations and more severe rendering problems and streamline the testing process even more.
Automated, comprehensive testing of enterprise applications takes significant time because regression tests evolve at an exponential rate. When we need to reduce the testing time drastically, parallel tests execute up to 5 times faster. Moreover, modern test automation tools allow parallel execution with a single command.
As automated tests are executed unattended or remotely in the cloud, an understanding of an error can become an issue for testers. Sometimes even detailed logs don’t guarantee to bring you up to date quickly.
Supporting failed test results with visuals makes automated testing life a lot easier. When we have a screenshot or video taken at the time an error occurred, it becomes much easier to recognize and describe an issue in detail.
We hope these practical suggestions will help you keep up and further improve your test automation efficiency and productivity. In addition to automated testing, implementing an Application Performance Management tool, like Stackify Retrace, can assist in improving the quality of your code. Try your free, two week trial of Retrace today.