About AI-Based Test Impact Analysis

About AI-Based Test Impact Analysis illustration

Running a full regression suite for every minor code change is a significant drain on time and resources, creating a major bottleneck in the CI/CD pipeline. Our AI-Based Test Impact Analysis service eliminates this inefficiency. By integrating with your code repositories, our AI engine analyzes recent commits to understand precisely which parts of the application have been modified. It then maps these changes to your existing test suite, intelligently identifying the exact subset of tests needed to validate the new code. This risk-based approach dramatically cuts down execution times, provides developers with faster feedback, and transforms your regression testing from a brute-force process into a smart, targeted, and efficient operation.

Our Framework

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Step 1

Code Repository Integration

We connect our AI tool to your source code repositories like Git or SVN. This allows the engine to monitor code changes in real-time, providing the foundational data needed for the impact analysis without disrupting your existing workflow.

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Step 2

Code and Test Case Mapping

The AI engine performs an initial scan to create a dependency map between your application's code and your entire test case repository. It learns which tests correspond to which functions, modules, and user-facing features across the app.

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Step 3

Real-Time Change Analysis

When a developer commits new code, the AI instantly analyzes the changes. It identifies all modified functions, methods, and dependencies, understanding the potential ripple effect these changes could have throughout the application.

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Step 4

Intelligent Test Selection

Based on the change analysis, the AI recommends a targeted list of test cases that must be executed to ensure full coverage of the modified areas. This prioritized list forms the optimized regression suite for that specific build.

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Step 5

Optimized Execution & Reporting

The selected test suite is automatically triggered in your CI pipeline. After execution, you receive a concise report detailing the code changes, the tests that were run, and the results, ensuring complete traceability and confidence.

Our Expertise

Our Expertise illustration
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Accelerate Build Validation by up to 90%

Stop waiting hours for regression results. By running only the essential tests, we reduce execution time from hours to minutes, giving your developers near-instant feedback.

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Optimize and Reduce Infrastructure Costs

Running fewer tests means less demand on your testing infrastructure. This leads to significant cost savings on cloud resources and virtual machine usage over time.

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Focus Testing on High-Risk Areas

Our AI ensures that testing efforts are concentrated where they matter most—on the parts of the application that have actually changed, maximizing defect detection.

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