1 citations · 1 across the 7 of their papers we have counts for
8 papers
DatalogBench: Evaluating Large Language Models on Text-to-Datalog Synthesis
Yuan Li, Hanyun Jiang, Guowei Tian +2
Datalog underpins reasoning tasks such as program analysis, but its programs are hard to write. Existing synthesizers automate this task but require users to state their intent as…
PyFlow: An Inter-procedural Static Analysis Framework for Python
Zinan Gu, Haoxiang Yan, Peisen Yao
Static program analysis infers program properties automatically. Yet precise interprocedural analysis remains challenging, and dynamically typed languages amplify the difficulty. P…
Accelerating C/C++ Pointer Analysis via Compiler-Based Offline Simplifications
Zinan Gu, Peisen Yao, Kui Ren
Pointer analysis is a cornerstone of numerous static analysis applications, including compiler optimizations, slicing, bug detection, and verification. While offline simplification…
A Fresh Look at Best Inductive Loop Invariant Synthesis for Bit-Vector Relations
Hanrui Zuo, Peisen Yao, Kui Ren
Synthesizing best inductive invariants (BII) is fundamental to program analysis and verification, yet existing approaches face significant efficiency challenges. We introduce a new…
Synthesizing Best Abstract Transformers via Parallel Bit-Vector Optimization
Weiqi Wang, Peisen Yao, Hanrui Zuo +3
Abstract interpretation provides a principled foundation for constructing sound static analyses through systematic abstraction. A central challenge is synthesizing the best abstrac…
HintPilot: LLM-based Compiler Hint Synthesis for Code Optimization
Hanyun Jiang, Peisen Yao, Kaiyue Li +3
Code optimization remains a core objective in software development, yet modern compilers struggle to navigate the enormous optimization spaces. While recent research has looked int…
KBX: Verified Model Synchronization via Formal Bidirectional Transformation
Jianhong Zhao, Yongwang Zhao, Peisen Yao +3
Complex safety-critical systems require multiple models for a comprehensive description, resulting in error-prone development and laborious verification. Bidirectional transformati…
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning (Extended Version)
Pingchuan Ma, Zhenlan Ji, Peisen Yao +2
Causal discovery is a powerful technique for identifying causal relationships among variables in data. It has been widely used in various applications in software engineering. Caus…