AI & ML Enhanced Automated Software Testing

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 on-premises 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.
• Speed up the remediation process using optional integration with OpenAI/Azure OpenAI providers 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 OpenAI/Azure OpenAI providers and using human-crafted prompts to refactor test cases in ways specific to the requirements outlined by the user.
• Target modified code and identify the right subset of tests to run to validate the changes using Jtest’s test impact analysis.

How It Works

With the combined power of on-premises AI and ML, here’s how our solution works.

• The Smart API Test Generator uses reasoning to analyze traffic patterns and create test scenarios that make the API calls represented by that traffic.
• Auto-configured test scenarios extract dynamic data from responses,  apply it to subsequent requests, and perform relevant assertions.
• ML learns business logic from API tests in your library to intelligently create or update test assets following company testing practices.
• The optional integration with OpenAI/Azure OpenAI providers analyzes service definitions and supports natural-language prompts to direct test generation, enabling teams to easily create meaningful API test scenarios that align with requirements.
• AI optimizes test execution to quickly validate application changes by identifying test cases impacted by code modifications and executing only the affected tests.

How It Works

Three common Selenium testing challenges application teams experience include:

1. Initial time and effort required to create tests.
2. High burden of maintaining tests.
3. Long test execution time.

Development teams efficiently achieve the following with Parasoft Selenic enhanced with AI/ML:

• Create JUnit or TestNG Selenium tests faster by recording user interactions during manual UI testing using the Parasoft Recorder.
• Reduce test case maintenance efforts and costs by healing Selenium test scripts during test execution through analysis of past successful test runs and adjusting the test case to use updated locators or extended wait conditions.
• Increase the stability of an existing Selenium test suite by applying Selenic’s recommendations for improved locators and wait conditions.
• Accelerate QA’s feedback to development by identifying and executing the specific subset of Selenium test cases that correlate to code modifications.

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.