1 citations · 2 across the 4 of their papers we have counts for
5 papers
Automatically Building Machine-Checked Assurance Cases from C Codebases to Requirements
Haokun Li, Zhongyi Wang, Guanyan Li +4
Large language models (LLMs) have shown promise in automating interactive theorem proving, yet verification of real-world C codebases requires more than discharging individual proo…
A Tale of 1001 LoC: Potential Runtime Error-Guided Specification Synthesis for Verifying Large-Scale Programs
Zhongyi Wang, Tengjie Lin, Mingshuai Chen +9
Fully automated verification of large-scale software and hardware systems is arguably the holy grail of formal methods. Large language models (LLMs) have recently demonstrated thei…
Preguss: It Analyzes, It Specifies, It Verifies
Zhongyi Wang, Tengjie Lin, Mingshuai Chen +5
Fully automated verification of large-scale software and hardware systems is arguably the holy grail of formal methods. Large language models (LLMs) have recently demonstrated thei…
PARF: An Adaptive Abstraction-Strategy Tuner for Static Analysis
Zhongyi Wang, Mingshuai Chen, Tengjie Lin +6
We launch Parf - a toolkit for adaptively tuning abstraction strategies of static program analyzers in a fully automated manner. Parf models various types of external parameters (e…
Parf: Adaptive Parameter Refining for Abstract Interpretation
Zhongyi Wang, Linyu Yang, Mingshuai Chen +6
The core challenge in applying abstract interpretation lies in the configuration of abstraction and analysis strategies encoded by a large number of external parameters of static a…