DEVOPSdigest

Parasoft has added Agentic AI capabilities to SOAtest, featuring API test planning and creation.

Parasoft also 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 assurance (QA) teams to fine-tune code quality.

"At Parasoft, our innovation has always centered on pragmatic automation that makes it easier for customers to build quality into every release," said Igor Kirilenko, chief product officer, Parasoft. "Our new Agentic AI capability reflects this mindset, helping users achieve faster, smarter outcomes. Likewise, our enhanced test impact analysis and code coverage aggregation—spanning automated and manual testing—helps teams meet their coverage goals with greater speed and agility."

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. In previous releases, Parasoft introduced the AI Assistant as an IDE-embedded intelligent chat interface to provide real-time technical guidance on tool usage and test creation. 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.

Equally important is the opportunity to capture code coverage from both automated testing and the manual testing that many teams still rely on, merging their coverage data in one place to create a holistic view of full application coverage. This lets manual testing teams contribute to the code coverage goals often owned by development teams. Coverage visibility across the application gives managers and team leads the insight needed to assess testing effectiveness, identify high-risk areas, and make informed decisions about resource allocation and quality priorities.

"QA is the last line of defense when it comes to safeguarding software quality," said Daniel Garay, director, Software Quality Assurance, Parasoft. "Efficiency is key. Enhanced code coverage across both automated and remaining manual tests is vital to keeping pace with development and getting quicker feedback, so we can confidently close all gaps and move forward with peace of mind."

In the latest CTP release, Parasoft expands its existing test impact analysis and coverage collection capabilities to manual testing workflows for Java and .NET applications. 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. Additionally, TIA removes the guesswork in identifying which test cases are critical for each application change. This gives manual testers confidence that they are testing the right functionality, so teams catch regressions sooner and keep bugs from reaching production.