Tricentis continues to build generative AI Copilots to strengthen its testing solutions. It has now launched a third Copilot. This time, qTest gets the addition. Previous Copilots have included the Testim Copilot and one for Tosca.
The qTest Copilot will enable users to simplify and accelerate test case generation using generative AI. In a recent blog, David Quintero, Sr. Technical Marketing Manager, explained what the new Copilot does. He wrote:
“qTest Copilot helps not only to simplify and accelerate test case generation but also builds stronger test coverage and higher quality releases. qTest Copilot broadens your testing scope by suggesting tests for new perspectives and unexpected scenarios.”
Anyone purchasing qTest now will automatically have access to the new Copilot. Existing users must upgrade to the new Tricentis qTest Enterprise AI version. It is not clear what impact this will have on pricing for users. Customers can request pricing, but the Tricentis website infers that it starts at $82 pupm when billed annually.
Mav Turner, Chief Product and Strategy Officer, Tricentis, commented, “Developer and QA teams today are looking to drive meaningful and measurable improvements to the test coverage of their applications, all while driving significant productivity gains.
“Feedback from our beta program suggests that qTest Copilot is enabling users to create complex test cases far more quickly than ever before, while also identifying gaps in test coverage that might have otherwise been overlooked. By automating these critical testing steps, teams can focus their efforts on higher-value activities, ultimately accelerating delivery timelines and improving overall software quality.”
What does qTest Copilot do?
The qTest Copilot will enable users to automatically draft test cases and test steps based on the source documents and user requirements fed into the LLM. Users can review these, but the time saved from having the Copilot generate these is potentially immense.
The Copilot is flexible, and it will enable users to quickly generate the standard test coverage for any application. It can also be used to fill potential gaps in the test schedules by calculating additional scenarios or tests for unexpected events.
The Copilot generates both the tests and the expected results within seconds, enabling QA teams to prepare applications for delivery faster than ever before. Tricentis estimates that the Copilot can reduce the time spent per case creation by up to 20 minutes. The additional test coverage and a higher quality of testing further add to the reasons why organisations should start leveraging the Copilot.
Tricentis revealed the initial capabilities as follows:
- Select and easily control which projects and users are enabled for qTest Copilot.
- Approve drafted test cases after modifying, deleting, or creating new steps as needed.
- Prompt qTest Copilot to summarize for more concise outputs or to elaborate with more details.
- Regenerate test steps or the entire test case without losing the overall test scope.
Tricentis is committed to driving further improvements into the qTest Copilot. It plans to add more functionality around test-case discovery. Using this users will map requirements to existing test cases, as well as test case and requirement review, which aims to analyse and improve the quality of existing assets in the qTest environment.
Enterprise Times: What does this mean
Is the third Copilot the last that Tricentis will launch? It seems unlikely, yet there are no other Copilots in their beta phase. As inferred above, Tricentis may just be looking to enhance the existing three Copilots.
For customers looking to understand more about the new qTest Copilot, Tricentis is hosting a webinar on November 21, 2024. Sensibly, it is streaming this at different times for different time zones.
Tricentis continues to invest in developing AI for its testing solutions. The decision is backed by its own research that revealed DevOps practitioners ranked testing as the most valuable (60%) area of AI investment across the software delivery lifecycle. The research also showed that AI-augmented DevOps tools could save teams over 40 hours per month. Gartner predicts that by 2027, the number of platform engineering teams using AI to augment every phase of the SDLC will have increased from 5% to 40%.
Anything that both saves time and improves the quality of software testing is welcome. The next step would be for Tricentis to leverage Agentic AI. One wonders where that is on its roadmap.
