Software test automation best practices to remember! Even when the economic convenience of automating a test task seems quite clear, it can still be difficult to determine the best way to deal with the transition to the automated process. Hp then suggests a best practice checklist to implement automated software testing processes that are truly effective against specific business needs.
1) Draw up a document with the test plan . Understanding the purpose of the application to be tested is essential for the success of the activity; this is why it is essential to carry out a preliminary planning to ensure that the test requirements are correctly implemented.
2) Divide the tests into ‘test cases’ to be automated . In all likelihood, it will not always be possible for companies to automate all the aspects outlined in the test plan. For this reason, automated testing should focus on complex, essential business processes associated with application functionality and for which they have been designed to meet the requirements.
3) Create automated tests . To exploit the technologies available today to create tests without having to perform scripting activities (there are commercially available tools capable of detecting the business process for the target application and allowing users to create test streams that can later be saved and reused ).
4) Expand testing coverage using integrated data table features: Testers can then create data-dependent tests that use specific keywords stored on spreadsheets to populate fields in an application. This capability allows testers to pass huge volumes of test data through the application.
5) Add tests to the tests . The actual criteria that determine the success or failure of a test should be added to the automated tests (to be able to carry out continuous checks on the test phases). The criteria include checks of the application front-end, middle tier or back-end database. The integrated database check confirms the values recorded in it and checks the accuracy of the transactions and the integrity of the data of the records that have been updated, deleted or added.