Two research papers from Stony Brook University’s Department of Computer Science were accepted to the 2026 ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), one of the leading international conferences in programming languages and programming systems research.
The papers were authored by Stony Brook faculty, graduate students and recent alumni, as well as external collaborators. Together, they represent two distinct areas of expertise within the department — software security and quantum computing — and highlight both the breadth of research being conducted at Stony Brook and the department’s growing presence in the programming languages community.
PLDI is considered a premier venue for programming languages research, bringing together researchers working on the design, implementation, theory and performance of programming systems.
One paper, “Analyzing Bytes: Pre-Disassembly Static Binary Analysis,” addresses a longstanding challenge in software analysis. Traditional approaches require software binaries to be translated into machine instructions before they can be studied, creating a significant bottleneck for applications such as cybersecurity, reverse engineering and performance optimization. The research team developed a new approach that analyzes all possible instruction locations simultaneously, making software analysis both faster and more accurate than previous methods.
This paper’s Stony Brook authors are Soumyakant Priyadarshan and Chencheng Jiang, both PhD students in computer science, and R. Sekar, SUNY Empire Innovation Professor and associate chair in the Department of Computer Science. Huan Nguyen, now at Google and a 2025 graduate of Sekar’s research group, presented the work at the conference.
The second paper, “SAQR-QC: A Logic for Scalable but Approximate Quantitative Reasoning about Quantum Circuits,” introduces a new framework for analyzing quantum circuits that are too large to represent in their entirety. Rather than attempting to model every component at once, the framework analyzes smaller groups of qubits while carefully tracking approximation errors, enabling rigorous analysis of increasingly complex quantum systems.
This paper was authored by Nengkun Yu, associate professor and SUNY Empire Innovation Scholar in the Department of Computer Science, in collaboration with Jens Palsberg of UCLA and Thomas Reps of the University of Wisconsin–Madison. Yu presented the research at PLDI 2026.
“It is encouraging to see two Stony Brook papers at PLDI this year, covering both binary analysis and quantum program reasoning,” said Yu. “These works reflect the range of programming-language research being developed in our department.”
The projects also reflect ongoing collaborative research efforts. The binary analysis work builds on research in software security and static binary analysis supported in part by the National Science Foundation and the Office of Naval Research. The quantum computing research stems from an ongoing collaboration among researchers at Stony Brook, UCLA and the University of Wisconsin–Madison focused on scalable verification methods for quantum software, supported in part by the National Science Foundation and DARPA.
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