Tapti Palit

Muhammad Farrukh, Baris Coskun, Tapti Palit et al.

Rust is a strong contender for a memory-safe alternative to C as a "systems" language, but porting the vast amount of existing C code to Rust remains daunting. In this paper, we evaluate the potential of large language models (LLMs) to automate the transpilation of C code to idiomatic Rust. We present SafeTrans, a generic framework that leverages LLMs to i) transpile C code into Rust, and ii) iteratively repair compilation and runtime errors. A key novelty of our approach is a few-shot guided repair technique for translation errors, which provides contextual information and example code snippets for specific error types, guiding the LLM toward the correct solution. Another novel aspect of our work is the evaluation of the security implications of the transpilation process, showing how some vulnerability classes in C persist in the translated Rust code. SafeTrans was evaluated with six leading LLMs on 2,653 C programs and two real-world C projects. Our results show that iterative repair improves the rate of successful translations from 54% to 80% for the best-performing LLM (gpt-4o).

Muhammad Farrukh, Baris Coskun, Tapti Palit et al.

Large-scale migration of legacy C code to Rust offers a promising path toward improving memory safety, but LLM-based C-to-Rust translation remains challenging due to limited context windows and hallucinations. Prior approaches are evaluated primarily on small programs or datasets skewed toward small codebases, providing limited insight into scalability on real-world systems. They also rely on static context construction, which breaks down in the presence of complex cross-module dependencies and often requires manual intervention. Recent coding agents offer a promising alternative through dynamic codebase navigation and context curation. When used out of the box, however, they frequently produce incomplete translations that appear superficially correct. We present ORBIT, an autonomous agentic framework for project-level C-to-Rust translation that combines dynamic context collection with dependency-guided orchestration and iterative verification. ORBIT constructs a dependency-aware translation graph, generates Rust interfaces, maps C functions to Rust counterparts, and coordinates multiple specialized agents. We evaluate ORBIT on 24 programs from CRUST-Bench, with 91.7% of the programs exceeding 1,000 lines of code. ORBIT achieves 100% compilation success and 91.7% test success in both expert-interface and automatically generated-interface settings, substantially outperforming C2Rust and CRUST-Bench, while reducing unsafe Rust code blocks to nearly zero. We further evaluate ORBIT on challenging cases from the DARPA TRACTOR benchmark, where it achieves competitive performance relative to participating systems.

Shenghsun Cho, Mrunal Patel, Basavaraj Kaladagi et al.

PCIe-connected FPGAs are gaining popularity as an accelerator technology in data centers. However, it is challenging to jointly develop and debug host software and FPGA hardware. Changes to the hardware design require a time-consuming FPGA synthesis process, and modification to the software, especially the operating system and device drivers, can frequently cause the system to hang, without providing enough information for debugging. The combination of these problems results in long debug iterations and a slow development process. To overcome these problems, we designed a VM-HDL co-simulation framework, which is capable of running the same software, operating system, and hardware designs as the target physical system, while providing full visibility and significantly shorter debug iterations.