arXiv AI By Chaoran Yuan, Fadi Kurdahi

FaultGene: LLM-Assisted Fault-Augmented Test Generation for Hardware-in-the-Loop Validation of Autonomous Driving Systems

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FaultGene is an LLM-assisted framework that automatically generates executable fault‑augmented tests for hardware‑in‑the‑loop validation of autonomous driving systems. It takes a baseline Scenic/CARLA scenario and a structured fault specification, then produces fault‑augmented test cases that reflect HIL‑level fault injection effects. The system refines candidates offline using semantic‑consistency checks and execution‑level feedback, enabling high‑quality test generation at deployment time without manual engineering or repeated refinement loops.

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arXiv AI
Jun 19

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

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.

By Ma Toan Bach, Yuchi Zheng, Haingo Razafindranto, Tanvir Alam, Aric Leather, Ranveer Sandhu, Jitesh Arora
arXiv AI
Aug 20

Coverage-Driven RTL Assertion Generation with Formal Exploration and Neuro-Symbolic Refinement

The paper introduces NeuroAssertion, a coverage-driven framework for generating RTL assertions that integrates formal trace generation, syntax-guided synthesis, and a two-step large language model (LLM) refinement process. It transforms hard-to-reach control-flow conditions into formal reachability goals, uses model checking to produce diverse traces, and mines initial assertions via SyGuS. The refinement stage employs one LLM to propose candidate assertions for uncovered regions and a second LLM to generate repair grammars that guide symbolic synthesis, resulting in roughly twice as many assertions and higher mutation coverage compared to traditional methods.

By Zhiyuan Yan, Ziyue Zheng, Hongce Zhang