HyperTest is actively evolving based on feedback from engineering teams. If there's a feature, integration, language, or workflow you'd like to see supported, we'd love to hear from you. Reach out to our team with your suggestions, and we'll use your feedback to help shape future releases.

HyperTest automatically detects changes to API behavior by comparing pull requests against previously observed runtime execution traces. If a change modifies a response structure, removes fields, or introduces breaking contract changes, HyperTest highlights the impact before the code is merged.

Most AI code review tools analyze source code and rely on static analysis to identify potential issues. HyperTest goes a step further by analyzing runtime execution traces to understand how code behaves in real environments. This allows it to catch production-impacting issues such as API contract breaks, race conditions, missing execution steps, authentication bypasses, and performance regressions.

Yes. HyperTest analyzes runtime execution flows across services, APIs, databases, and infrastructure dependencies. This allows it to understand how requests move through your system and identify changes that could impact downstream consumers, even when those interactions involve authenticated services.

Review the affected execution path and the supporting evidence provided by HyperTest. Each finding includes the impacted services, execution flow, and potential production risk. Once the issue is resolved, simply update the pull request and HyperTest will automatically re-analyze the changes.

You can contact our team directly through our support channels. Whether you've discovered a bug, need help with an integration, or have ideas for new functionality, we're always looking for feedback from engineering teams using HyperTest.

HyperTest focuses on production-impacting issues that often escape traditional code reviews, including: 1. API contract breaks 2. Race conditions 3. Removed idempotency checks 4. Authentication and authorization issues 5. Silent execution path changes 6. Cross-service dependency failures 7. Performance regressions 8. Database query inefficiencies Every finding is backed by runtime evidence collected from real execution traces.

HyperTest surfaces findings directly in your pull request workflow and provides detailed context through the HyperTest dashboard. Engineers can review affected execution paths, impacted systems, and recommended remediation steps before merging code.

HyperTest continuously compares new code changes against previously observed runtime behavior. When a pull request alters an execution path, API contract, dependency interaction, or critical business workflow, HyperTest identifies the difference and highlights the potential impact before deployment.

Verify that runtime traces are being collected from your application environment and that the relevant workflows have been executed. HyperTest relies on execution evidence to understand system behavior. If traces are available but expected code paths are not being analyzed, contact the HyperTest team for assistance.

Yes. HyperTest is designed for distributed systems and microservices environments. It tracks how requests move across services, databases, caches, queues, and external dependencies, helping teams understand the full impact of code changes before they reach production.

Absolutely. HyperTest is particularly valuable in microservices environments where changes in one service can create unexpected downstream effects. By analyzing runtime execution traces across services, HyperTest helps teams identify contract breaks, dependency issues, and production risks that are difficult to detect through static analysis alone.