Presentation
From Broken Regression to Root-Cause Commit in One Click A Two-Stage Regression-Aware Git-Bisect Framework for Large-Scale Hardware Verification
DescriptionLarge-scale hardware verification relies on massive regression testing across thousands of tests, seeds, and configurations. When a previously passing regression begins to fail, identifying the exact code change that introduced the failure is extremely difficult due to non-determinism, merge commits, and the absence of a known clean baseline. Traditional debugging methods require engineers to manually inspect large commit histories, often taking days or weeks and leading to ambiguity in fault attribution.
This work presents a two-stage regression-aware root-cause isolation framework that automatically identifies the precise commit responsible for a regression failure. The framework first locates a valid good baseline within the commit history using regression-validated inputs, and then performs controlled, deterministic isolation between the good and bad states to find the first failing commit. The approach is fully merge-aware, supports non-deterministic regressions, and integrates directly into production regression flows. All decisions are validated using real regression results and logged for full auditability.
The framework reduces root-cause identification from weeks to hours, eliminates manual guesswork, and provides reliable commit-level failure attribution for large-scale verification environments.
This work presents a two-stage regression-aware root-cause isolation framework that automatically identifies the precise commit responsible for a regression failure. The framework first locates a valid good baseline within the commit history using regression-validated inputs, and then performs controlled, deterministic isolation between the good and bad states to find the first failing commit. The approach is fully merge-aware, supports non-deterministic regressions, and integrates directly into production regression flows. All decisions are validated using real regression results and logged for full auditability.
The framework reduces root-cause identification from weeks to hours, eliminates manual guesswork, and provides reliable commit-level failure attribution for large-scale verification environments.
Event Type
Engineering Poster
TimeTuesday, July 285:00pm - 6:00pm PDT
LocationDAC Pavilion, Exhibit Floor