AI Test Automation Tools for Real-World Workflows

How It Works

A common roadblock to adopting static analysis tools successfully is managing a large number of warnings and handling perceived false positives. Whatever the compliance requirements—MISRA, CWE, OWASP, and more—our automated static analysis tools enhanced with AI and ML flag and prioritize the rule violations that the team needs to fix first.

A hotspot detection engine works with an advanced AI-based model to assign violations to developers matching their best skills and experience—learning from violations they fixed in the past.

Our patented AI and ML enhanced static analysis solutions offer the following benefits:

• Reduce static analysis noise by grouping violations to fix or ignore based on past triage actions.
• Accelerate the remediation of static analysis findings by grouping violations according to root cause analysis.
• Enhance the developer experience by assigning violations to specific team members based on their history of fixing violations in the past.
• Use CVE match analysis to see probability projections on the likelihood of reported SAST violations being real vulnerabilities or false positives.
• Speed up the remediation process using optional integration with various LLM providers like OpenAI, Azure OpenAI, and Copilot to suggest code fixes.

How It Works

Java development teams can use Parasoft Jtest enhanced with AI to create high-quality unit tests and increase code coverage with the following capabilities:

• Rapidly generate high-quality unit test suites for uncovered Java code using bulk test creation to quickly improve code coverage metrics.
• Enhance and customize unit tests with one-click actions to increase test maintainability, parameterize test cases, and add assertions for regression control.
• Easily identify modified code in the user’s IDE and generate new unit tests to target and fill coverage gaps, increasing code coverage.
• Automatically generate mocks and stubs to isolate the code under test with minimal effort.
• Maintain security and privacy by using Parasoft’s proprietary AI to create and update unit tests completely on premises, with no data leaving the user’s environment.
• Customize unit tests by leveraging Jtest’s optional integration with various LLM providers like OpenAI and Azure OpenAI and using human-crafted prompts to refactor test cases in ways specific to the requirements outlined by the user.
• Target modified code and automatically identify and execute the right subset of tests to run to validate code changes with Jtest’s IDE-based Live Unit Testing or with CLI-based test impact analysis.

How It Works

Automated testing processes speed up the testing feedback loop, which, in turn, speeds up the remediation of identified defects. Here’s what teams can accomplish using TIA, Parasoft’s AI-optimized regression solution.

• Developers and test engineers execute tests impacted by changes locally in their IDE, accelerating the feedback loop to validate code modifications faster without waiting for feedback from nightly regression runs.
• DevOps teams that integrate Parasoft’s TIA technology into the CI/CD pipeline reduce the number of automated tests to be executed for pull requests, allowing them to validate changes to the application under test more quickly.