Digital business creates a strong drive for companies that haven’t traditionally thought of themselves as software companies to become more like software companies. One strong need continues to be how to drive greater amounts of test automation. We see two primary paths that have emerged and as we work on updating our Magic Quadrant for Software Test Automation this creates fundamental choices in tools.
Option 1: Become more like a software company or your favorite internet devops prototype. In this case your path is to use developers or testers with development skills to build tests. Typically these tests will be built using tools like Selenium and associated frameworks. The advantages are Se is open source gaining a lot of community support, it connects into the devops toolchain readily including storage of the tests in the same repository that the code is stored in. The disadvantage is you are writing code to test your code meaning tester need stronger development skills and it can be less efficient. This generally means hiring new testers with these skills the Software Development Test Engineer that is being frequently sought after.
Option 2: Is more of a move forward with the people and skills we have. This means I need to find ways to make non-developer testers effective at automation. This has been a long running challenge leading to a number of often failed attempts. Record and playback is a great example. It demos well and you can get automation but it won’t be maintainable and doesn’t easily translate to a good understanding of the quality of the test suite. For most organizations, outside of wholly new business units (e.g. building a new mobile app team) this is the reality we have potentially hundreds of employed testers who have solve business process knowledge but for which an approach to automation is raw coding/scripting is not viable. Here is where we see growing importance of frameowkrks, model based approaches and machine learning playing a critical roll.
We would love to hear your thoughts and success/failure stories either here or on the Gartner Client discussion portal. The need to automate is becoming critical please join the conversation.