3 citations · 9 across the 13 of their papers we have counts for
12 papers · 1 filter
AgentArcEval: An Architecture Evaluation Method for Foundation Model based Agents
Qinghua Lu, Dehai Zhao, Yue Liu +6
The emergence of foundation models (FMs) has enabled the development of highly capable and autonomous agents, unlocking new application opportunities across a wide range of domains…
Bridging Solidity Evolution Gaps: An LLM-Enhanced Approach for Smart Contract Compilation Error Resolution
Likai Ye, Mengliang Li, Dehai Zhao +2
Solidity, the dominant smart contract language for Ethereum, has rapidly evolved with frequent version updates to enhance security, functionality, and developer experience. However…
SHIELDA: Structured Handling of Exceptions in LLM-Driven Agentic Workflows
Jingwen Zhou, Jieshan Chen, Qinghua Lu +2
Large Language Model (LLM) agentic systems are software systems powered by LLMs that autonomously reason, plan, and execute multi-step workflows to achieve human goals, rather than…
When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction
Zhenchang Xing, Yang Liu, Zhuo Cheng +4
With the growing capabilities of large language models (LLMs), they are increasingly applied in areas like intelligent customer service, code generation, and knowledge management.…
Think Like an Engineer: A Neuro-Symbolic Collaboration Agent for Generative Software Requirements Elicitation and Self-Review
Sai Zhang, Zhenchang Xing, Jieshan Chen +5
The vision of End-User Software Engineering (EUSE) is to empower non-professional users with full control over the software development lifecycle. It aims to enable users to drive…
SeeAction: Towards Reverse Engineering How-What-Where of HCI Actions from Screencasts for UI Automation
Dehai Zhao, Zhenchang Xing, Qinghua Lu +2
UI automation is a useful technique for UI testing, bug reproduction, and robotic process automation. Recording user actions with an application assists rapid development of UI aut…
Evaluation-Driven Development and Operations of LLM Agents: A Process Model and Reference Architecture
Boming Xia, Qinghua Lu, Liming Zhu +3
Large Language Models (LLMs) have enabled the emergence of LLM agents, systems capable of pursuing under-specified goals and adapting after deployment. Evaluating such agents is ch…
Swiss Cheese Model for AI Safety: A Taxonomy and Reference Architecture for Multi-Layered Guardrails of Foundation Model Based Agents
Md Shamsujjoha, Qinghua Lu, Dehai Zhao +1
Foundation Model (FM)-based agents are revolutionizing application development across various domains. However, their rapidly growing capabilities and autonomy have raised signific…
CasModaTest: A Cascaded and Model-agnostic Self-directed Framework for Unit Test Generation
Chao Ni, Xiaoya Wang, Liushan Chen +4
Though many machine learning (ML)-based unit testing generation approaches have been proposed and indeed achieved remarkable performance, they still have several limitations in eff…
From Misuse to Mastery: Enhancing Code Generation with Knowledge-Driven AI Chaining
Xiaoxue Ren, Xinyuan Ye, Dehai Zhao +2
Large Language Models (LLMs) have shown promising results in automatic code generation by improving coding efficiency to a certain extent. However, generating high-quality and reli…
Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation
Chao Ni, Xin Yin, Kaiwen Yang +3
Though many deep learning (DL)-based vulnerability detection approaches have been proposed and indeed achieved remarkable performance, they still have limitations in the generaliza…
SeeHow: Workflow Extraction from Programming Screencasts through Action-Aware Video Analytics
Dehai Zhao, Zhenchang Xing, Xin Xia +3
Programming screencasts (e.g., video tutorials on Youtube or live coding stream on Twitch) are important knowledge source for developers to learn programming knowledge, especially…