Company CEO Oren Rubin said the Testim Development Kit makes it possible to call capabilities such as the ability to record user interface interactions via an application programming interface (API).
The Testim approach to applying artificial intelligence (AI) testing differs from rivals in that Testim allows DevOps teams to fully inspect how algorithms construct a test, he noted. DevOps teams can also customize those algorithms to fit their own requirements, which is critical when it comes time for DevOps to explain how tests were conducted as part of a compliance audit.
Testim will continue to provide access to its platform via a graphical user interface, but with the edition of the SDK, Rubin said his company expects to see an increase in the number of DevOps teams that will incorporate Testim within the context of continuous development/continuous deployment (CI/CD). Once that occurs, the number of tests those teams will be willing to run against software before it’s deployed in a production environment should also increase, especially as more developers leverage APIs to create their own tests, Rubin said. That doesn’t eliminate the need for another set of eyes to test an application, but it should reduce the number of common errors made before any piece of code is tested by someone else on the DevOps team.
One of the most time-consuming elements of any DevOps process is the time it takes to create tests for each application. The Testim platform employs machine learning algorithms to discover the entire application environment and then begin creating appropriate tests. As DevOps teams modify those tests, the Testim platform continues to learn how to build tests the way the DevOps team prefers.
The Testim platform doesn’t eliminate the need for testing expertise on the DevOps team, but it does enable organizations to scale their testing processes by augmenting whatever testing expertise they have on hand to reduce bottlenecks and improve overall software quality. Those algorithms also provide the added benefit of never taking a day off or quitting to take a more lucrative position elsewhere.
When it comes to AI, there is naturally a lot of fear and loathing. On the one hand, IT professionals become concerned AI will replace them. On the other hand, they are often disappointed when machine learning algorithms don’t instantly automate a process to their satisfaction. It takes a significant amount of time for algorithms to learn how any IT environment operates, with each update to that environment requiring those algorithms to discover new functions. At this juncture, it’s not a question of whether AI will play a role in DevOps processes, but rather to what degree. Given the repetitive nature of testing, Testim is betting application testing will prove to be an area that lends itself to AI sooner than later.