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Luiz Lemos do Valle

dblp:398/1283 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 50% Program synthesis and code generation · 50%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program synthesis and code generation
code translation
1.012026
C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques · IEEE Trans. Software Eng. 2026
Software maintenance and evolution › software reengineering › software modernization › software migration › language migration
c-to-rust translation
1.012026
C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques · IEEE Trans. Software Eng. 2026
Software maintenance and evolution › software reengineering › software modernization › software migration
language migration
1.012026
C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques · IEEE Trans. Software Eng. 2026
Program synthesis and code generation › code translation
LLM-based code translation
1.012026
C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques · IEEE Trans. Software Eng. 2026
Systems and software security
memory safety
0.312026
C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques · IEEE Trans. Software Eng. 2026

Methods — techniques the papers use, named apart from their topics

rule-based translation · 2.0large language model · 2.0end-to-end testing · 2.0
YearPublicationVenuePosition
2026 C2SaferRust: Transforming C Projects Into Safer Rust With NeuroSymbolic Techniques
abstract
In recent years, there has been a lot of interest in converting C code to Rust, to benefit from the memory and thread safety guarantees of Rust. C2Rust is a rule-based system that can automatically convert C code to functionally identical Rust, but the Rust code that it produces is non-idiomatic, i.e., makes extensive use of unsafe Rust, a subset of the language thatdoesn’thave memory or thread safety guarantees. At the other end of the spectrum are LLMs, which produce idiomatic Rust code, but these have the potential to make mistakes and are constrained in the length of code they can process. In this paper, we present C2SAFERRUST, a novel approach to translate C to Rust that combines the strengths of C2Rust and LLMs. We first use C2Rust to convert C code to non-idiomatic, unsafe Rust. We then decompose the unsafe Rust code into slices that can be individually translated to safer Rust by an LLM. After processing each slice, we run end-to-end test cases to verify that the code still functions as expected. We also contribute a benchmark of 7 real-world programs, translated from C to unsafe Rust using C2Rust. Each of these programs also comes with end-to-end test cases. On this benchmark, we are able to reduce the number of raw pointers by up to 38%, and reduce the amount of unsafe code by up to 28%, indicating an increase in safety. The resulting programs still pass all test cases. C2SAFERRUST also shows convincing gains in performance against two previous techniques for making Rust code safer.
Vikram Nitin, Rahul Krishna, Luiz Lemos do Valle, Baishakhi Ray
IEEE Trans. Software Eng.3