6 tips about automatic testing

Test automation not only reduces costs and effort, but also helps speed up the site. In this article, we share how to automate testing to keep the automated testing initiative on track with key tips on testing, designing, and maintaining large enterprise applications.

Use appropriate test automation tools

Each test automation project has its own needs. The right tool can significantly reduce test time and improve the performance of the test team. The wrong tool can create unnecessary complexity. Choose from all the required devices, browsers, operating system versions, mobile platforms, test automation level required (UI, API, database tests), test types (functional, load, localization) and detection technology (native) native), image, text) support. With a single tool, the learning curve to provide automation is significantly reduced, and similar scripts are reused for different platforms. In addition, we recommend that you use the following checklists for your pre-selected tools: General requirements Does the technical team have the required skills? Does the flexibility of the framework give the team more capabilities? Does your test team have experience working with this tool? Does the tool have a strong community that helps with accurate resources, users, and documentation? How responsive are you to the issues that arise? Provides accurate auto test reports? Will it integrate with CI tools, problem management tools, test management tools, and communication tools used in the project? Special requirements Does this tool allow distributed testing? How long does the test take? Does it support smart expectations? How does it help simplify test changes? Does it support the DDT approach? Code separation from data (DDT approach) Many test automation engineers tend to store test data (input, output, validation) along with code. This method overloads the code with several iterations when new tests are added. It also significantly complicates test code maintenance, especially if the automated test program undergoes repeated changes. To solve these challenges, we recommend that you use DDT (data-driven testing) methods and organize all the test data into tables in separate files (database file, Excel spreadsheet, etc.). The DDT approach reduces the time required to create new tests and increases accuracy because test engineers can easily reuse the same test data in different tests and avoid errors due to improved test code. Maximize API testing Test automation is usually accompanied by automated testing via the UI. However, testing through the UI is relatively time consuming. UI tests can only be created near the end of a software development project. In addition, the UI is prone to frequent changes, even in the final stages. We recommend that API testing take precedence over performance testing. APIs are available earlier than the development cycle and remain fully stable. In addition, the API test can be run in seconds, while the GUI test takes two minutes to run. Use of visual testing in cross-browser testing (and highly dynamic content) Modern applications are required to run on various browsers, operating systems, and devices. This may cause bugs due to rendering inconsistencies. We prefer to eliminate visual inconsistencies using screenshots. Compare screenshots with samples to confirm that the page or object appears exactly as expected. We especially like AI-based tools for visual testing (Applitools are the most popular) because they can differentiate between accepted changes and more severe rendering problems and make the testing process even easier. Parallel testing Comprehensive and automated testing of organizational programs takes considerable time. When we need to drastically reduce test time, parallel tests run up to 5 times faster. In addition, automated testing tools make parallel execution possible with a single command. Have error reports supported by screenshots / videos taken at error time Because automated tests run unattended or remotely in the cloud, misunderstanding can be problematic for testers. Sometimes even accurate reports do not guarantee that updates will be delivered to you quickly. Support for failed test results visually makes automated testing much easier. When we take screenshots or videos of an error, it becomes much easier to identify and describe the details of the issue. Conclusion We hope these practical suggestions help you maintain and further improve the efficiency and productivity of automated testing. In addition to automated testing, implementing application performance management tools, such as Stackify Retrace, can help improve the quality of your code.