PhD Thesis Proposal - Zunchen Huang
Fri, Dec 02, 2022 @ 09:00 AM - 11:00 AM
PhD Candidate: Zunchen Huang
Title: Constraint Based Analysis for Persistent Memory Programs
Time: Friday, December 2, 9:00 AM-11:00 AM PST
Committee: Chao Wang (chair), William GJ Halfond, Mukund Raghothaman, Srivatsan Ravi, and Pierluigi Nuzzo.
Abstract: Emerging persistent memory (PM) technologies are beginning to bridge the gap between volatile memory and non-volatile storage in computer systems, by allowing high-speed memory access, byte-addressability, and persistency at the same time. However, PM programming remains a challenging and error-prone task due to reliance on ordinary developers to write correct and efficient PM software code. In this presentation, I propose a framework to detect and repair PM bugs in software code automatically using a set of new symbolic analysis techniques. Unlike existing methods, which rely on patterns and heuristics to detect and repair a small subset of PM bugs, the proposed symbolic analysis framework is able to handle a wide range of PM bugs uniformly. This is achieved by first encoding the program semantics, correctness properties, and PM requirements as a set of logical constraints, and then solving these constraints using off-the-shelf solvers. By reasoning about these logical constraints symbolically, our method can detect, diagnose, and repair PM bugs both efficiently and automatically. It can also infer PM requirements automatically. Finally, I will discuss potential extensions of the framework to programs that rely on both PM and multi-threading to reason about persistency and concurrency simultaneously.
Zoom link: https://usc.zoom.us/j/4326990557
WebCast Link: https://usc.zoom.us/j/4326990557
Audiences: Everyone Is Invited
Contact: Lizsl De Leon