Cover Image

Enhancing Semantic Understanding in Pointer Analysis using Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Baijun, Wang, Kailong, Shi, Ling, Wang, Haoyu, Guo, Yao, Li, Ding, Chen, Xiangqun
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Boosting Pointer Analysis With LLM-Enhanced Allocation Function Detection
by: Cheng, Baijun, et al.
Published: (2025)

Semantic-Enhanced Indirect Call Analysis with Large Language Models
by: Cheng, Baijun, et al.
Published: (2024)

SliceLocator: Locating Vulnerable Statements with Graph-based Detectors
by: Cheng, Baijun, et al.
Published: (2024)

Understanding the Effectiveness of Coverage Criteria for Large Language Models: A Special Angle from Jailbreak Attacks
by: Zhou, Shide, et al.
Published: (2024)

Drowzee: Metamorphic Testing for Fact-Conflicting Hallucination Detection in Large Language Models
by: Li, Ningke, et al.
Published: (2024)

NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-level Semantic Slicing
by: Zhou, Shide, et al.
Published: (2024)

The Effect of Pointer Analysis on Semantic Conflict Detection
by: Barbosa, Matheus, et al.
Published: (2025)

Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection
by: Li, Yuxi, et al.
Published: (2024)

Beyond Fidelity: Explaining Vulnerability Localization of Learning-based Detectors
by: Cheng, Baijun, et al.
Published: (2024)

GroupTuner: Efficient Group-Aware Compiler Auto-Tuning
by: Gao, Bingyu, et al.
Published: (2025)

SPOLRE: Semantic Preserving Object Layout Reconstruction for Image Captioning System Testing
by: Liu, Yi, et al.
Published: (2024)

Understanding Large Language Model Supply Chain: Structure, Domain, and Vulnerabilities
by: Hu, Yanzhe, et al.
Published: (2025)

Large Language Models are overconfident and amplify human bias
by: Sun, Fengfei, et al.
Published: (2025)

SeeWasm: An Efficient and Fully-Functional Symbolic Execution Engine for WebAssembly Binaries
by: He, Ningyu, et al.
Published: (2024)

Context-Sensitive Pointer Analysis for ArkTS
by: Yang, Yizhuo, et al.
Published: (2026)

Large Language Models for Software Engineering: A Systematic Literature Review
by: Hou, Xinyi, et al.
Published: (2023)

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
by: Rao, Hongzhou, et al.
Published: (2025)

LEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models
by: Wang, Yan, et al.
Published: (2025)

Towards an Understanding of Large Language Models in Software Engineering Tasks
by: Zheng, Zibin, et al.
Published: (2023)

Formally Verified Binary-level Pointer Analysis
by: Verbeek, Freek, et al.
Published: (2025)

Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models
by: Wang, Yan, et al.
Published: (2024)

Bridging Code Graphs and Large Language Models for Better Code Understanding
by: Chen, Zeqi, et al.
Published: (2025)

Large Language Model Supply Chain: A Research Agenda
by: Wang, Shenao, et al.
Published: (2024)

MiniScope: Automated UI Exploration and Privacy Inconsistency Detection of MiniApps via Two-phase Iterative Hybrid Analysis
by: Wang, Shenao, et al.
Published: (2024)

DistillSeq: A Framework for Safety Alignment Testing in Large Language Models using Knowledge Distillation
by: Yang, Mingke, et al.
Published: (2024)

WaDec: Decompiling WebAssembly Using Large Language Model
by: She, Xinyu, et al.
Published: (2024)

Beyond Correctness: Exposing LLM-generated Logical Flaws in Reasoning via Multi-step Automated Theorem Proving
by: Zheng, Xinyi, et al.
Published: (2025)

Enhanced LLM-Based Framework for Predicting Null Pointer Dereference in Source Code
by: Sultan, Md. Fahim, et al.
Published: (2024)

MeTMaP: Metamorphic Testing for Detecting False Vector Matching Problems in LLM Augmented Generation
by: Wang, Guanyu, et al.
Published: (2024)

LLM4Perf: Large Language Models Are Effective Samplers for Multi-Objective Performance Modeling
by: Wang, Xin, et al.
Published: (2025)

LogPTR: Variable-Aware Log Parsing with Pointer Network
by: Wu, Yifan, et al.
Published: (2024)

Decoding Secret Memorization in Code LLMs Through Token-Level Characterization
by: Nie, Yuqing, et al.
Published: (2024)

Models Are Codes: Towards Measuring Malicious Code Poisoning Attacks on Pre-trained Model Hubs
by: Zhao, Jian, et al.
Published: (2024)

Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
by: Wang, Zhijie, et al.
Published: (2024)

Reverse Engineering User Stories from Code using Large Language Models
by: Ouf, Mohamed, et al.
Published: (2025)

Advancing Code Coverage: Incorporating Program Analysis with Large Language Models
by: Yang, Chen, et al.
Published: (2024)

DCE-LLM: Dead Code Elimination with Large Language Models
by: Chen, Minyu, et al.
Published: (2025)

BinMetric: A Comprehensive Binary Analysis Benchmark for Large Language Models
by: Shang, Xiuwei, et al.
Published: (2025)

Flow Sensitivity without Control Flow Graph: An Efficient Andersen-Style Flow-Sensitive Pointer Analysis
by: Zhang, Jiahao, et al.
Published: (2025)

Enchanting Program Specification Synthesis by Large Language Models using Static Analysis and Program Verification
by: Wen, Cheng, et al.
Published: (2024)