Are you on the hunt for a test automation tool, but there are just so many factors to consider? Some tools have an overwhelming amount of features, and it can be hard to remember what should be at the core of a good test automation tool. Here at Virtuoso, we’ve compiled a list of 9 criteria that should be considered - the more of these that a tool fulfills, the smarter your automation will be. Let’s jump into it:
A good tool should test the Application Under Test (AUT) like a real-world user; this way you get the best part of manual testing in your smart automation tool. Test environments and simulations tend to be inaccurate and don’t mirror real-world scenarios. When a tool tests the AUT through the methods used by the end-user, it has a higher chance of uncovering bugs and preventing incidents in production. For this, the tool needs to work with the application through user-available channels like button clicks, scrolling, etc. rather than working with underlying scripts.
For example, if you want to type in a field that isn’t visible in the frame and requires scrolling down, the tool should physically scroll down to the field and type in whatever you told it to. Because of the difference in privacy laws in different regions, application behavior can be a bit funky, so testing needs to adapt. One way it can do this is by testing across multiple geographical locations through the cloud instead of simulating IP locations.
Robotic Process Automation (RPA) is essentially configuring software processes to complete a given job through automation, and it’s gaining ground in its popularity. A good tool should be able to deploy multiple backend processes (virtual robots) simultaneously to accomplish testing. This negates the problem of scalability and time dependence on human resources. At any given moment, hundreds, or even thousands, of these virtual robots should be able to crawl the application looking for bugs or providing test coverage.
Brittle object identification is a common, but important, issue with traditional test automation. Testers usually associate objects with some identification properties or xPaths. With even a slight change in these properties, the script is unable to identify the object and throws a failure. A smart test tool should overcome this issue through a number of intelligent techniques. The tool can use a combination of multiple object properties or keep track of the surrounding objects to identify an element. In the event of one property changing dynamically at run time, the tool should be able to identify the element using the combination of the other properties.
There are many interesting ways that intelligent objects identification works. For example, a login button is always placed in the vicinity of the username and password text boxes. If a tool is unable to identify the login button through a descriptive property it can look for the username and password text boxes and find out if the login button is present nearby.
This one is short and sweet: the less setup and onboarding time needed, the better. If a testing team is being pushed up against a deadline, the last thing they need is to spend a month learning how to use a tool and ensure it’s installed properly. A smart testing tool that is hosted on the cloud eliminates setup time, and one that uses Natural Language Programming (NLP) decreases onboarding time drastically.
There are a near-infinite amount of sources to get information from; the last thing you need is another one. A good automation tool should be able to integrate with platforms like Slack, Jenkins, Microsoft Teams, GitHub, and more. Even better if you can set up more integrations on your own.
We just published a post on cross-browser testing, so we won’t spend too much time on it here. But cross-browser testing is vital to test accessibility, design, responsiveness, and basic functionality.
A good testing tool should be able to easily scale to the user’s needs and business size. After all, you want an automated tool to be able to grow with your business. There are two other features that play a part in scalability: cloud capabilities and NLP.
There are several advantages to using cloud-based testing software, which we’ve written about in a previous post, but we’ll go over some basics here. We mentioned earlier that the cloud eliminates setup and installation, saving time, but it can also execute scalable tests. By testing over the cloud, the tests can also be deployed over physical systems. The cloud also makes testing more secure.
NLP can benefit teams in numerous ways, chiefly that NLP can make test authoring so much faster and anyone on the team is able to author tests. This accessibility to testing also makes tests scalable because anyone can work on them. Plus, we talked earlier about how NLP can slash onboarding times.
Ok, that was a lot to get through! Choosing the right test automation software can be tricky, and a “good” tool may have some of these features. But a great tool will have all of them! So here’s our Virtuoso plug: Virtuoso tests in the same way as an end user would with plain English. There’s no installation required, and execution is instantly started on the cloud from the push of a button! Virtuoso self-heals its tests and executes on every browser, OS, and device combination out there without having to change anything. We also integrate with the majority of the CI/CD tools, so anyone can sign up and start executing with Virtuoso right away! Plus, we have something for everyone: whether you’re looking for functional testing, API testing, or both, we’ve got you covered. Book a demo with us to see how Virtuoso, the smart automation testing tool, can empower you to put quality first!