1 citations · 1 across the 9 of their papers we have counts for
11 papers
How Do Coding Agents Optimize Software and Report Performance Validation? A Large-Scale Empirical Study of Open-Source Pull Requests
Huiyun Peng, Ricardo Calvo, Kelechi G. Kalu +1
Software performance optimization requires identifying bottlenecks and improvement opportunities, and empirically evaluating the effects and trade-offs across performance objective…
Model-Based Agentic Software Engineering
James C. Davis, Kelechi Kalu, Huiyun Peng +1
Coding agents increase implementation capacity without automatically making project intent, system structure, or acceptance evidence explicit. As implementation becomes abundant re…
Beyond Local Code Optimization: Multi-Agent Reasoning for Software System Optimization
Huiyun Peng, Parth Vinod Patil, Antonio Zhong Qiu +2
Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven…
How Do Agents Perform Code Optimization? An Empirical Study
Huiyun Peng, Antonio Zhong, Ricardo Andrés Calvo Méndez +2
Performance optimization is a critical yet challenging aspect of software development, often requiring a deep understanding of system behavior, algorithmic tradeoffs, and careful c…
AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents
Erik Pautsch, Tanmay Singla, Parv Kumar +6
LLM-based agents are rapidly proliferating, yet the infrastructure for discovering, evaluating, and governing them remains fragmented compared to mature ecosystems like software pa…
A Guide to Stakeholder Analysis for Cybersecurity Researchers
James C Davis, Sophie Chen, Huiyun Peng +2
Stakeholder-based ethics analysis is now a formal requirement for submissions to top cybersecurity research venues. This requirement reflects a growing consensus that cybersecurity…
SysLLMatic: Large Language Models are Software System Optimizers
Huiyun Peng, Arjun Gupte, Ryan Hasler +7
Automatic software system optimization can improve software speed, reduce operating costs, and save energy. Traditional approaches to optimization rely on manual tuning and compile…
Recommending Pre-Trained Models for IoT Devices
Parth V. Patil, Wenxin Jiang, Huiyun Peng +7
The availability of pre-trained models (PTMs) has enabled faster deployment of machine learning across applications by reducing the need for extensive training. Techniques like qua…
Can Large-Language Models Help us Better Understand and Teach the Development of Energy-Efficient Software?
Ryan Hasler, Konstantin Läufer, George K. Thiruvathukal +5
Computing systems are consuming an increasing and unsustainable fraction of society's energy footprint, notably in data centers. Meanwhile, energy-efficient software engineering te…
Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions
Huiyun Peng, Arjun Gupte, Nicholas John Eliopoulos +8
Energy-efficient software helps improve mobile device experiences and reduce the carbon footprint of data centers. However, energy goals are often de-prioritized in order to meet o…
ZTD: Mitigating Software Supply Chain Vulnerabilities via Zero-Trust Dependencies
Paschal C. Amusuo, Kyle A. Robinson, Tanmay Singla +5
Third-party libraries like Log4j accelerate software application development but introduce substantial risk. Vulnerabilities in these libraries have led to Software Supply Chain (S…