UNIVERSITY PARK, Pa. — Linhai Song, assistant professor in the Penn State College of Information Sciences and Technology, is the recipient of a 2022 Faculty Early Career Development (CAREER) award from the National Science Foundation (NSF). The CAREER award is the most prestigious award given by the NSF in support of junior faculty members who exemplify the role of teacher-scholar through outstanding research, excellent teaching, and the integration of education and research.
The five-year, $550,000 award will advance Song’s work to improve the toolchain design of Rust, a young programming language designed to implement safe and efficient systems software. Rust outperforms the more widely known C and C++ languages in memory safety and concurrent programming — when two or more threads are running at the same time. Song hopes that his work will encourage more programming in Rust, leading to safety in software systems in the next few decades.
“Rust is known to have a steep learning curve and to be difficult to program in reality; programmers can easily write code violating Rust’s safety rules (and that is) rejected by the Rust compiler,” said Song. “This award will support our efforts to pinpoint the difficulties in learning and programming Rust and build effective techniques for a better coding experience.”
With this award, Song specifically aims to identify programming challenges caused by Rust’s existing safety checks and develop novel visualization techniques to resolve them, improve the effectiveness of existing testing input generation techniques, accelerate existing dynamic detection of bugs — unexpected problems with the software — and failure diagnosis techniques, and build automated techniques to fix bugs captured by Rust’s safety checks.
“Although we can apply existing techniques built for C/C++ to Rust programs, since these techniques were not invented for Rust and they are not aware of Rust’s language features, applying them directly will inevitably lose efficiency and effectiveness,” said Song. “The funded project will improve these existing techniques on Rust programs to complement Rust’s safety checks, capture more safety issues and generate a more secure Rust ecosystem.”
Song joined the College of IST in 2017 after starting his career as a staff research scientist at FireEye Inc. He earned a bachelor’s degree from Huazhong University of Science and Technology, a master’s degree from the Chinese Academy of Sciences in 2010, and a doctorate from the University of Wisconsin-Madison. His research interests include tool support for improving the reliability, security and efficiency of software systems.