This three-year, $349,999 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new techniques for automated lemma synthesis in interactive theorem provers. Specifically, the University of California, Los Angeles will reduce the lemma synthesis problem to a form of data-driven program synthesis, generating input-output examples from the current proof state to ensure generated lemmas target the user's goal. The project will...
This $611,492 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program to the University of Texas at Austin focuses on developing neurosymbolic AI techniques to enhance the accessibility and efficiency of interactive formal theorem provers. The goal is to automate the low-level aspects of theorem-proving, enabling wider use of formal verification tools for applications like safer software, more robust hardware, and...
This $719,494 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at the University of California, San Diego (UCSD) to develop more scalable and general synthesis algorithms for the field of program synthesis. The project builds on a recent framework called SemGuS (Semantics-Guided Synthesis) to enable the synthesis of larger software systems by composing smaller modular components. The...
The National Science Foundation awarded a $275,000 Project Grant to the University of Texas at Austin under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support the development of program synthesis techniques to help software developers manage schema changes to databases. The project aims to simplify the schema modification process through automated techniques for migrating data between formats and updating code to reflect schema...
The National Science Foundation awarded a $800,000 Project Grant to the University of Texas at Austin under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support the development of a neurosymbolic program-synthesis framework that closely couples deep learning and classical symbolic methods for program synthesis. Researchers will explore new learning algorithms exposing neural models of code to explicit knowledge about program semantics....
The National Science Foundation awarded $544,003 to Carnegie Mellon University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for a three-year Project Grant beginning October 1, 2022. The grant aims to develop formal libraries, methods, and tools to carry out tasks like encoding statements as clausal formulas and reducing search spaces in verified ways using automated reasoning and interactive theorem proving. Specifically, the university will...
The National Science Foundation (NSF) awarded a Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Davis (UC Davis) for the project "EAGER: PROOF-CARRYING CODE COMPLETIONS." The $300,000 award, with a project period running from February 15, 2024 to July 31, 2025, will support the development of tools, techniques, and empirical results for using large language models to generate trustworthy code completions...
This three-year National Science Foundation project grant of $418,380 supports research at the University of Wisconsin-Madison to develop a neurosymbolic framework for semantics-aware program synthesis. Funded under the NSF's Computer and Information Science and Engineering program (CFDA 47.070), the award period runs from August 1, 2022 to July 31, 2025. Specifically, the university researchers will couple large neural models trained on source code with symbolic methods from formal methods to...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program award, with a total funding of $175,000, supports the development of novel verification methodologies to enhance software quality, safety, and security for safety-critical and security-critical applications such as self-driving cars and digital medical services. The project aims to develop verification techniques based on first-order assertions and auxiliary logical variables,...
This $875,000 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to the University of California, San Diego (UCSD). The project aims to develop new techniques for aligning large language models (LLMs) with formal specifications in order to generate high-quality computer code that provably matches user intent. Specifically, the project will: (1) develop grammar-aligned decoding...