Parasoft has added Agentic AI capabilities to SOAtest, featuring API test planning and creation. Parasoft also has enhanced its Continuous Testing Platform (CTP), extending Test Impact Analysis (TIA) and code coverage collection to manual testers, further reducing technical barriers, accelerating feedback, and improving collaboration between development and quality. Parasoft SOAtest’s AI Assistant now utilizes agentic AI in API test-scenario generation, making it easier for testing teams with diverse skill sets to adopt API test automation. This release now enables a tester to, in natural language, request the AI to generate API test scenarios using service definition files. Going beyond simple test creation, the AI Assistant leverages AI agents to generate test data and parameterize the test scenario for data looping. Complex, multi-step workflows with dynamic data are handled in collaboration with the user, allowing less technical testers to build complicated tests without requiring scripts, advanced code-level skills, or in-depth domain knowledge. In addition to reducing technical burdens, Parasoft’s AI Assistant will help customers scale API testing and automate other in-product actions. As additional agents are introduced over time, it will produce even smarter test scenarios and workflow guidance. QA teams can leverage Parasoft CTP to collect and analyze code coverage from manual test runs, then publish that coverage into Parasoft DTP for deeper analysis. In CTP, the tester can easily create a manual test case, and with a few clicks can ensure code coverage is captured during their test runs. With this visibility, teams can fine-tune their manual testing efforts—eliminating redundancies, filling coverage gaps, and focusing on the highest-risk areas. Teams can now create, import, and manage manual tests directly in CTP, capture code coverage as those tests run, and utilize that data in test impact analysis to pinpoint exactly which manual regression tests need to be rerun to validate application changes. This trims retesting time and effort, reducing testing fatigue while strengthening collaboration between development and QA teams. This new capability also makes it easier to adapt manual regression testing for agile sprints, as it allows teams to only focus on impacted areas. With faster test cycles, QA teams can quickly validate changes and shorten feedback loops.