Loved by Developers
AI Test Engineer for Modern Backends
Captures run-time behavior to review new code changes to catch functional problems that tools like Coderabbit will miss
Production issues get never revealed at PR
Current code review tools insufficient…
Noise > Signal. More than 80% of comments either not actionable or just plain useless
Report non-critical issues. Style suggestions, optimisations, subjective opinions i.e. good-to-know issues that don't break production
Static code analysis lacks context. it reads syntax patterns. Can't catch bugs that surface when code actually runs
Feedback is shallow. See only what changed not why, making comments generic or misleading
👉 Developers can spend less time fixing issues, only if all of them get reported at every PR?
Enter HyperTest
Agent that reviews behavior not just code
Agent that reviews behavior not just code
What it does: Code review
Unlike traditional tools that guess at potential problems, HyperTest tells you exactly how your changes will impact real API behavior in production. It's like having a senior engineer who has deep knowledge of how your system actually runs reviewing every line of code. Traditional code review tools analyze code statically using pattern-matching rules, while HyperTest learns from watching your APIs actually execute live.
How it's different: powered by runtime execution
Captures traces of the complete execution flow of API requests—every function call, database query, and external service interaction. By comparing traces from your main branch against your new code, HyperTest predicts precisely what will change in production behavior
Github Summary
This approach essentially brings the rigor of production monitoring and observability into the code review process, creating a new category of "runtime-informed static analysis" that bridges the gap between traditional code review and production impact assessment
Zero to Live at Lightning Speed
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