Parasoft recently released the 2024.1 releases of several of its products, including Java testing tool Jtest, C# and .NET testing tool dotTEST, and testing analytics solution DTP.
Jtest now includes test templates in Unit Test Assistant, which is a feature that uses AI to generate a suite of tests. With the, testers get more control over the structure of their test classes and can specify common configurations that their tests require.
Jtest can also now run test impact analysis right from within the IDE. Whenever a code change is made, Jtest will identify and execute tests and provide feedback to the developer on the impact of their modifications.
“With the new Jtest release, developers get real-time insights into which tests are impacted by their code changes,” Igor Kirilenko, chief product officer at Parasoft, told SD Times. “While you are still modifying your code, Jtest automatically runs the relevant tests and delivers instant feedback. This groundbreaking feature not only saves time but also ensures that potential bugs are caught and fixed before they ever reach the build pipeline.”
In Jtest and dotTEST, an integration with OpenAI/Azure OpenAI Service provides AI-generated fixes for flow analysis violations.
Jtest and dotTEST also now support the latest version of the Common Weakness Enumeration (CWE) list, 4.14. Additionally, both have improved out-of-the-box static analysis test configurations.
And finally, DTP’s integration with OpenAI/Azure OpenAI Service speeds up remediation of security vulnerabilities by matching security rule violations to known vulnerabilities, and then coming up with a probability score of the likelihood of each being a real vulnerability or a false positive.
“Developers often face significant cognitive load when triaging static analysis violations, particularly those related to security,” Jeehong Min, technical product manager at Parasoft, told SD Times. “Each security rule comes with its own learning curve, requiring time to understand its nuances. To assist developers, Parasoft DTP offers recommendations powered by pre-trained machine learning models and models that learn from the development team’s triage behavior. The ultimate goal is to help developers make informed decisions when triaging and remediating static analysis violations.”
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