AI in software testing: What does it mean?
(1) Many organizations continue to rely heavily on manual testing and aging technology, but market conditions demand a shift to automation, as well as more intelligent testing that is context-aware.
Gartner anticipates (1) vendors (...) to deliver automated test design, test generation, and advanced test result analytics. These expanded capabilities will help to make testing accessible to a wider range of user personas, including those that do not have deep test automation expertise.
(1) AI-augmented test creation can occur in many different ways. Examples include the use of models or domain-specific languages to define application functionality and the associated tests in a way that enables these tests to be automatically generated.
Xray, the leader in Jira-Native Test Management, recently added Test Case Designer to its Xray Enterprise offering to help QA teams tackle complex testing scenarios involving extensive datasets with sophisticated test case generation algorithms to eliminate repetitive, redundant scenarios, while ensuring no coverage gaps. Have you ever wondered, “How many tests are enough?”. Well, Xray provides the answer. Reach up to 100% critical interaction coverage in the fewest possible tests.
(1) Gartner “Market Guide for AI-Augmented Software-Testing Tools”
