This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $375,000 to the University of Utah will fund the development of practical formal methods to capture the correctness expectations of numerical algorithm designers as formal requirements. The project aims to create formal models capable of representing non-standard hardware and bridging its behavioral differences to present uniform higher-level...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award provides $366,160 to the University of Rochester to develop practical formal methods for capturing numerical algorithm correctness expectations, formal models for non-standard hardware, and end-to-end correctness verification techniques. The goal is to help adapt numerical solvers to new problems and hardware, resolving the data/numerics...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) will fund a $1,200,000 project to develop practical, systematic fuzzing tools that enhance the security of scientific software. The 3-year project, led by the University of Utah, aims to address vulnerabilities in complex, multi-language scientific software by introducing (1) performant cross-language instrumentation, (2) automated...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant award of $600,000 to Yale University will leverage the Rust programming language to enhance the correctness and reliability of systems software, such as operating systems. The project aims to develop innovative techniques for intralingual resource representation, design patterns for verifiable operating system implementation, and a hybrid approach combining formal and informal...
The University of Utah received a $220,500 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This 5-year award, beginning March 1, 2024, supports research to develop scalable security testing techniques for large software systems. The project focuses on advancing "fuzzing" - a predominant software vulnerability detection method - to address the unique challenges posed by software...
The University of Massachusetts Lowell's Office of Research Administration received a $600,000 three-year Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070). The grant funds research to develop mechanisms for detecting soft errors and silent data corruption in high-performance computing systems. The university will apply compressive sensing and machine learning techniques, including unsupervised anomaly detection, to...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program grant, awarded under CFDA 47.070, supports the University of Utah's research project titled "SLES: HIGH-CONFIDENCE GUARANTEES FOR SAFE REWARD AND POLICY LEARNING UNDER UNCERTAINTY." The $439,425 award, effective August 15, 2024 through July 31, 2027, aims to develop scalable learning methods that are robust to uncertainty, enable self-assessment, and provide test cases for assessing...
The National Science Foundation awarded Princeton University $1,118,988 under the Computer and Information Science and Engineering program (CFDA 47.070) for a three-year project grant titled "COLLABORATIVE RESEARCH: FMITF: TRACK I: FORMALLY VERIFIED NUMERICAL METHODS." The grant aims to advance the development of formally verified numerical methods through a layered approach integrating reasoning about numerical software correctness and accuracy from mathematics to software code....
This $360,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to improve the reliability and performance of parallelizing compilers by automatically verifying that translated parallel code has the same functionality as the original sequential code. The project will involve precise modeling of sequential and parallel program behavior, developing a verification tool, and mathematically proving the...
This Project Grant from the National Science Foundation Division of Computer and Network Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $517,545 in funding to the University of Utah from January 1, 2022 to September 30, 2024. The award supports research to advance software vulnerability detection techniques. Specifically, the university researchers will develop new approaches to fuzz testing, a method for identifying software...