Project Grant 2541857
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, aims to simplify and automate the verification of high-performance distributed systems. The $375,000 award to the Regents of the University of Michigan, to be completed by September 2027, will develop new techniques such as message invariants and distributed ownership types to make formal verification of complex, real-world distributed systems more...
- 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 Project Grant award of $387,341 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to extend auto-active verification techniques to enable the verification of security and privacy properties, known as hyperproperties, for software systems. The key objectives of the three-year project are to: 1) develop new deductive logics and algebras to support automated reasoning about relationships between...
- The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a $593,022 Project Grant to The Trustees of the Stevens Institute of Technology in Hoboken, New Jersey. This grant, under NSF's Computer and Information Science and Engineering (CFDA 47.070) program, supports a project focused on developing new formal verification techniques for concurrent software. The project aims to bridge the gap between intuitive scenario-based reasoning and rigorous...
- This Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop practical formal methods for capturing the correctness expectations of numerical algorithm designers as formal requirements, as well as formal models for simulating non-standard hardware while bridging their behavioral differences. The $375,000 award to the University of Utah will fund research to carry out end-to-end...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $174,999 to Monmouth University Inc. to develop a formal verification framework for precisely analyzing the behavior of software systems that use mutable arrays. The research aims to expand the capabilities of existing relational reasoning techniques to handle a broader range of security, privacy, and efficiency properties, particularly for programs...
- This Project Grant award, with a total funding of $375,000.00, was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award aims to simplify and automate the verification of high-performance distributed systems, which are crucial but complex. The project will develop new techniques, such as "message invariants" and "distributed ownership types," to make formal verification of real-world,...
- This National Science Foundation project grant supports research into composable verification of crash-safe distributed systems through Grove, a new approach that allows modular formal verification of distributed system components in the presence of crashes. With a total award amount of $249,998, the grant runs from March 15, 2023 through May 31, 2026. The work directly addresses challenges in reasoning about crash recovery in distributed systems where individual nodes can crash and reboot, as...
- This $900,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop "pay-as-you-go" technology for verifying consistency properties of distributed system designs. The objective is to reduce the burden of using formal methods to prove consistency guarantees, enabling more widespread adoption and enabling the creation of more reliable distributed systems. The project will implement...
- Cornell University was awarded a $381,012 Project Grant from the National Science Foundation (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support research to formally verify the correctness and accuracy of numerical software used in applications such as planetary modeling, self-driving vehicles, rocketry, wireless technology, and medicine. The researchers will take a layered...
CAREER: SPECIFYING AND VERIFYING CORRECTNESS OF SOFTWARE UPDATES -SOFTWARE UPDATES ARE A FACT OF LIFE, YET THEY ARE DIFFICULT FOR DEVELOPERS TO GET RIGHT BECAUSE THE NEW VERSION MUST CORRECTLY INTERACT WITH THE PREVIOUS VERSION. INCORRECT UPDATES REMAIN A SURPRISINGLY COMMON SOURCE OF CATASTROPHIC FAILURES IN PRACTICE. FORMAL VERIFICATION, A TECHNIQUE WHERE SOFTWARE IS MATHEMATICALLY PROVEN TO BEHAVE AS INTENDED, IS A PROMISING APPROACH TO MAKE SOFTWARE MORE RELIABLE; HOWEVER, WITH EXISTING VERIFICATION APPROACHES, WE DON'T KNOW HOW TO STATE (MUCH LESS PROVE) COMPATIBILITY. THIS PROJECT'S NOVELTIES ARE TO DEVELOP A DEFINITION OF SOFTWARE UPDATE CORRECTNESS AND CREATE THE PROOF TECHNIQUES TO SHOW THAT UPDATES ARE CORRECT BEFORE DEPLOYING THEM. THE PROJECT'S IMPACTS ARE NEW VERIFICATION TOOLS THAT CAN BE USED TO PROVE AN UPDATE IS COMPATIBLE, AND ULTIMATELY AN UNDERSTANDING OF UPDATE CORRECTNESS THAT LEADS TO MORE RELIABLE SYSTEMS. VERIFYING UPDATES IS ESPECIALLY IMPORTANT WITH INCREASED USE OF AI-BASED CODING AGENTS, WHICH WILL PRODUCE MORE RELIABLE CHANGES IF THEY HAVE FEEDBACK ON WHETHER AN UPDATE IS COMPATIBLE WITH THE ALREADY DEPLOYED CODE OR NOT. UPDATE CORRECTNESS IS ALSO IMPORTANT FOR UPDATES TO MACHINE LEARNING (ML) INFRASTRUCTURE ITSELF, WHICH IS ALSO RAPIDLY CHANGING. WE IDENTIFY THREE FUNDAMENTAL UPDATE ISSUES TO FOCUS ON IN THIS PROJECT: DATA-FORMAT COMPATIBILITY, SPECIFYING THE EFFECT OF DATA MIGRATION ON A SYSTEM'S BEHAVIOR, AND VERIFYING DISTRIBUTED-SYSTEM ROLLING UPGRADES. THE APPROACH WE TAKE IS TO DEVELOP SPECIFICATIONS FOR WHAT A COMPATIBLE UPDATE IS IN EACH OF THESE CASES: THE SPECIFICATION IS A DESIRED PROPERTY OF THE NEW CODE THAT CONSIDERS ANY DATA THAT MIGHT BE PRODUCED BY THE OLD CODE. NEXT, WE DEVELOP A PROOF TECHNIQUE FOR PROVING THESE NEW SPECIFICATIONS IN PERENNIAL, A PROGRAM LOGIC FOR THE GO PROGRAMMING LANGUAGE THAT USES MACHINE-CHECKED PROOFS. FINALLY, WE WILL APPLY THE TECHNIQUES TO SEVERAL EXAMPLES OF UPDATES THAT ARE REPRESENTATIVE OF REAL-WORLD CHANGES. THE GOAL IS TO LAY THE FORMAL FOUNDATIONS FOR AN IMPORTANT ASPECT OF SOFTWARE CORRECTNESS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | ($382k) | 7/10/26 | ||
| Not listed | $381.6k | 4/3/26 |