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20242026
most citedBinPRE: Enhancing Field Inference in Binary Analysis Based Protocol Reverse Engineering

1 citations · 2 across the 8 of their papers we have counts for

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7 papers · 1 filter

cs.SE2026

CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?

Hang He, Li Wang, Hao Chen +9

Static-analysis checker synthesis requires agents to interpret a defect specification, inspect a repository, implement analyzer-specific logic, and refine the checker through repea…

cs.SE2026

Clarity Is Not Assumed: Understanding LLM-Based Code Generation under Ambiguous Requirements

Di Yang, Xinou Xie, Xiuwen Yang +7

Software requirement ambiguity is ubiquitous in real-world development, stemming from the inherent imprecision of natural language and the varying interpretations of stakeholders.…

cs.SE2026

Improving Random Testing via LLM-powered UI Tarpit Escaping for Mobile Apps

Mengqian Xu, Yiheng Xiong, Le Chang +3

Random GUI testing is a widely-used technique for testing mobile apps. However, its effectiveness is limited by the notorious issue -- UI exploration tarpits, where the exploration…

cs.SE2026

FLARE: Agentic Coverage-Guided Fuzzing for LLM-Based Multi-Agent Systems

Mingxuan Hui, Xinyue Li, Lu Wang +7

Multi-Agent LLM Systems (MAS) have been adopted to automate complex human workflows by breaking down tasks into subtasks. However, due to the non-deterministic behavior of LLM agen…

cs.SE2025

Automated detection of atomicity violations in large-scale systems

Hang He, Yixing Luo, Chengcheng Wan +3

Atomicity violations in interrupt-driven programs pose a significant threat to software reliability in safety-critical systems. These violations occur when the execution sequence o…

cs.SE2024★ 1 cited

BinPRE: Enhancing Field Inference in Binary Analysis Based Protocol Reverse Engineering

Jiayi Jiang, Xiyuan Zhang, Chengcheng Wan +3

Protocol reverse engineering (PRE) aims to infer the specification of network protocols when the source code is not available. Specifically, field inference is one crucial step in…

cs.SE2024★ 1 cited

Are LLMs Correctly Integrated into Software Systems?

Yuchen Shao, Yuheng Huang, Jiawei Shen +3

Large language models (LLMs) provide effective solutions in various application scenarios, with the support of retrieval-augmented generation (RAG). However, developers face challe…