https://scholarworks.unist.ac.kr/handle/201301/26 2026-04-08T21:03:36Z 2026-04-08T21:03:36Z Hong, Jaemin Ryu, Sukyoung https://scholarworks.unist.ac.kr/handle/201301/91290 2026-04-07T03:32:30Z 2024-09-30T15:00:00Z

Title: Type-migrating C-to-Rust translation using a large language model Author(s): Hong, Jaemin; Ryu, Sukyoung Abstract: Rust, a modern system programming language, introduces new types that prevent memory bugs and data races. This makes translating legacy system programs from C to Rust a promising approach to enhance their reliability. Since manual code translation is time-consuming, it is desirable to automate the translation. To yield satisfactory results, the translator should have the ability to perform type migration, i.e., removing C types and introducing Rust types in the code. In this work, we aim to automatically port an entire C program to Rust by translating each C function to a Rust function with a signature containing proper Rust types through type migration. This goal is challenging because (1) type migration cannot be achieved through syntactic mappings between type names, and (2) after type migration, function bodies should be correctly restructured based on the precise understanding of the functions' behavior. To address these difficulties, we leverage large language models (LLMs), which possess knowledge of program semantics and programming idioms. However, na & iuml;vely instructing LLMs to translate each function produces unsatisfactory Rust code, containing unmigrated or improperly migrated types and a huge number of type errors. To resolve these issues, we propose three techniques: (1) generating candidate signatures, (2) providing translated callees' signatures to LLMs, and (3) iteratively fixing type errors using compiler feedback. Our evaluation shows that the proposed approach yields a 63.5% increase in migrated types and a 71.5% decrease in type errors compared to the baseline (the na & iuml;ve LLM-based translation) with modest performance overhead.

2024-09-30T15:00:00Z Hong, Jaemin Ryu, Sukyoung https://scholarworks.unist.ac.kr/handle/201301/91279 2026-04-07T02:46:20Z 2025-10-31T15:00:00Z

Title: Automatically Translating C to Rust Author(s): Hong, Jaemin; Ryu, Sukyoung Abstract: Legacy system programs developed in C have suffered from prevalent memory bugs. Migrating these systems to Rust is a promising way to enhance reliability, thanks to Rust’s strong safety guarantee. Due to the high cost of manual migration, automatic C-to-Rust translators are essential for enabling the migration of real-world systems. However, existing translators generate unsatisfactory code by relying on language features whose safety is not validated by the compiler and code patterns considered unidiomatic by Rust developers. To improve the quality of automatic translation, static analysis and code transformation can be employed to replace unsafe features and unidiomatic patterns with safe and idiomatic alternatives. This article discusses the research community’s efforts to address scalar pointers, locks, unions with tags, and output parameters, and introduces remaining unsafe features and unidiomatic patterns that future work should tackle. Furthermore, we explore the potential of using large language models for C-to-Rust translation.

2025-10-31T15:00:00Z Han, J. Heo, S. Lee, G. Bang, W. -C. Kim, D. K. Kim, C. Y. https://scholarworks.unist.ac.kr/handle/201301/91221 2026-04-06T08:23:05Z 2011-01-31T15:00:00Z

Title: 6-DOF tracker using LED directivity Author(s): Han, J.; Heo, S.; Lee, G.; Bang, W. -C.; Kim, D. K.; Kim, C. Y. Abstract: Proposed is a new concept for a 6-DOF optical tracker exploiting the directivity of an LED. To verify the concept, a low-noise, linear optical sensor was designed, a working prototype was built that solves a source-localisation problem in real time, and its performance, compared with a reference tracker, was evaluated.

2011-01-31T15:00:00Z Han, Jaehyun Choi, Sangwon Heo, Seongkook Lee, Geehyuk https://scholarworks.unist.ac.kr/handle/201301/91220 2026-04-06T08:23:04Z 2012-09-30T15:00:00Z

Title: Optical touch sensing based on internal scattering in touch surface Author(s): Han, Jaehyun; Choi, Sangwon; Heo, Seongkook; Lee, Geehyuk Abstract: While diffuse-illumination touch sensing has the advantage of being sensitive enough to detect an object over a touch surface, it has the drawback of being unable to distinguish touches from approaches reliably. As a solution to this problem, proposed is a novel optical sensing structure that exploits the phenomenon of internal scattering. A prototype touch surface realising the proposed concept confirmed that it is indeed effective for better touch classification while retaining proximal sensitivity.

2012-09-30T15:00:00Z