Library-Aware Doubles and Iterative Repair for Large Language Model-Generated Unit Tests in OpenSIL Firmware 文章

ArXiv CS.AI2026-06-19NEWSen作者: Ma Toan Bach, Yuchi Zheng, Haingo Razafindranto, Tanvir Alam, Aric Leather, Ranveer Sandhu, Jitesh Arora

详细信息

来源站点
ArXiv CS.AI
作者
Ma Toan Bach, Yuchi Zheng, Haingo Razafindranto, Tanvir Alam, Aric Leather, Ranveer Sandhu, Jitesh Arora
文章类型
NEWS
语言
en
发布日期
2026-06-19

摘要

arXiv:2606.19725v1 Announce Type: cross Abstract: Validating changes in low-level C firmware is expensive because unit tests (UTs) are fragile under strict build constraints, where missing headers, unresolved symbols, and dependency mismatches frequently prevent compilation and linking. This study introduces an automated UT authoring workflow for the Open-Source Silicon Initialization Library (openSIL) firmware codebase maintained by Advanced Micro Devices (AMD) that reduces manual effort through a large language model (LLM) guided multi-agent pipeline. The workflow combines automated generation of test scaffolds, library-aware creation or reuse of stubs, mocks, and fakes, and an iterative compile-dispatch repair loop driven by build logs and line-coverage feedback. We evaluate the approach using compilation success, repair iterations, dispatch success, and line coverage, with time, cost, and token usage as secondary measures.