Abstract
A system related to automated testing gap categorization and codebase vulnerability localization in large-scale distributed computing environments. The system may receive an incident record containing unstructured text and identifiers pointing to external systems, obtain content from the external systems based on the identifiers, and aggregate the content into a unified context payload. The system may generate a fingerprint data structure based on the unified context payload and a versioned analysis prompt to determine whether AI model analysis is needed. The system may perform multi-stage AI analysis including identifying where a supervised analysis system indicated a testing gap, classifying the type of testing gap using a hierarchical taxonomy, and using timestamps to isolate one or more code commits that caused the incident. The system may verify the existence of the code commits and generate a visualization of the testing gap.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Singh, Aman, "System and Method for Automated Testing Gap Categorization and Codebase Vulnerability Localization", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10237