Automation Tests - Best Practices

It’s a danger to consider automation just as a routine task to be completed. Automation should be considered as an integral part of delivering a quality end product and the focus should be consistently on designing and developing relevant test suites. Below set of practices would come in handy.

Design Tests Before Automating Them

We need to keep in mind that test design has to be of prime importance. A well designed test is what finds the bug. The tests and scenarios needs to be clearly defined before start of test automation.

Foccus on the big picture

The objective of automation is not passing the test or making it work. The focus should be on producing a quality deliverable and hence the scope of testing should not be compromised for making the automation tests work.

Consistent and stable tests

We should be able to rely on the automation test results as the automation regression suite gives confidence to the team. Unstable tests that produce inconsistent results should not be part of the automation test suite.

Use testing techniques

Using testing techniques - Boundary Value Analysis, Equivalence Partitioning, and State Transition, while designing tests can greatly increase the value of the tests.

Manual testing vs Automation

When transitioning from a manual tester to automation test developer avoid trying to automate every single test scenario. Automation tests should be written based on the business critical scenarios and considering the objectives of test automation.

Review tests

To avoid redundant tests in the test suite it is a good practice to review the tests constantly (maybe in every sprint) so that the relevancy of the test suite can be maintained.

Create tests that take data sets as inputs

Hard coding data into the tests is never a good idea. When tests can accept different data combinations from data sheets , maintaining the tests becomes a much easier job.

Use data sets in tests according to business rules

Rather than using random data, tests should take data based on conditions. For example selection of date, can be tested by grouping input data into holidays, weekdays, weekends.