19 citations · 73 across the 32 of their papers we have counts for
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Still Manual? Automated Linter Configuration via DSL-Based LLM Compilation of Coding Standards
Zejun Zhang, Yixin Gan, Zhenchang Xing +5
Coding standards are essential for maintaining consistent and high-quality code across teams and projects. Linters help developers enforce these standards by detecting code violati…
PTMPicker: Facilitating Efficient Pretrained Model Selection for Application Developers
Pei Liu, Terry Zhuo, Jiawei Deng +4
The rapid emergence of pretrained models (PTMs) has attracted significant attention from both Deep Learning (DL) researchers and downstream application developers. However, selecti…
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…
Explore-Construct-Filter: An Automated Framework for Rich and Reliable API Knowledge Graph Construction
Yanbang Sun, Qing Huang, Xiaoxue Ren +3
The API Knowledge Graph (API KG) is a structured network that models API entities and their relations, providing essential semantic insights for tasks such as API recommendation, c…
Architectural Patterns for Designing Quantum Artificial Intelligence Systems
Mykhailo Klymenko, Thong Hoang, Xiwei Xu +4
Utilising quantum computing technology to enhance artificial intelligence systems is expected to improve training and inference times, increase robustness against noise and adversa…
DesignRepair: Dual-Stream Design Guideline-Aware Frontend Repair with Large Language Models
Mingyue Yuan, Jieshan Chen, Zhenchang Xing +6
The rise of Large Language Models (LLMs) has streamlined frontend interface creation through tools like Vercel's V0, yet surfaced challenges in design quality (e.g., accessibility,…
Automated Soap Opera Testing Directed by LLMs and Scenario Knowledge: Feasibility, Challenges, and Road Ahead
Yanqi Su, Zhenchang Xing, Chong Wang +4
Exploratory testing (ET) harnesses tester's knowledge, creativity, and experience to create varying tests that uncover unexpected bugs from the end-user's perspective. Although ET…
A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems
Dawen Zhang, Xiwei Xu, Chen Wang +2
Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled wid…
From Exploration to Revelation: Detecting Dark Patterns in Mobile Apps
Jieshan Chen, Zhen Wang, Jiamou Sun +5
Mobile apps are essential in daily life but frequently employ deceptive patterns, such as visual emphasis or linguistic nudging, to manipulate user behavior. Existing research larg…
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…
A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model
Jingwen Zhou, Qinghua Lu, Jieshan Chen +4
The rapid advancement of AI technology has led to widespread applications of agent systems across various domains. However, the need for detailed architecture design poses signific…
An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping
Boming Xia, Qinghua Lu, Liming Zhu +1
The advent of advanced AI underscores the urgent need for comprehensive safety evaluations, necessitating collaboration across communities (i.e., AI, software engineering, and gove…
Let's Discover More API Relations: A Large Language Model-based AI Chain for Unsupervised API Relation Inference
Qing Huang, Yanbang Sun, Zhenchang Xing +5
APIs have intricate relations that can be described in text and represented as knowledge graphs to aid software engineering tasks. Existing relation extraction methods have limitat…
Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective
Dawen Zhang, Boming Xia, Yue Liu +6
The advent of Generative AI has marked a significant milestone in artificial intelligence, demonstrating remarkable capabilities in generating realistic images, texts, and data pat…
Towards a Responsible AI Metrics Catalogue: A Collection of Metrics for AI Accountability
Boming Xia, Qinghua Lu, Liming Zhu +3
Artificial Intelligence (AI), particularly through the advent of large-scale generative AI (GenAI) models such as Large Language Models (LLMs), has become a transformative element…
Let's Chat to Find the APIs: Connecting Human, LLM and Knowledge Graph through AI Chain
Qing Huang, Zhenyu Wan, Zhenchang Xing +4
API recommendation methods have evolved from literal and semantic keyword matching to query expansion and query clarification. The latest query clarification method is knowledge gr…
Pop Quiz! Do Pre-trained Code Models Possess Knowledge of Correct API Names?
Terry Yue Zhuo, Xiaoning Du, Zhenchang Xing +4
Recent breakthroughs in pre-trained code models, such as CodeBERT and Codex, have shown their superior performance in various downstream tasks. The correctness and unambiguity of A…
A Taxonomy of Foundation Model based Systems through the Lens of Software Architecture
Qinghua Lu, Liming Zhu, Xiwei Xu +3
The recent release of large language model (LLM) based chatbots, such as ChatGPT, has attracted huge interest in foundation models. It is widely believed that foundation models wil…