119 citations · 253 across the 10 of their papers we have counts for
10 papers
When AI Takes the Wheel: Security Analysis of Framework-Constrained Program Generation
Yue Liu, Zhenchang Xing, Shidong Pan +1
In recent years, the AI wave has grown rapidly in software development. Even novice developers can now design and generate complex framework-constrained software systems based on t…
Protect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
Yue Liu, Chakkrit Tantithamthavorn, Li Li
Recent years have witnessed the emerging trend of extensions in modern Integrated Development Environments (IDEs) like Visual Studio Code (VSCode) that significantly enhance develo…
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
Xinyu She, Yue Liu, Yanjie Zhao +5
Modern language models (LMs) have been successfully employed in source code generation and understanding, leading to a significant increase in research focused on learning-based co…
Large Language Models for Software Engineering: A Systematic Literature Review
Xinyi Hou, Yanjie Zhao, Yue Liu +7
Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE ta…
Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues
Yue Liu, Thanh Le-Cong, Ratnadira Widyasari +4
We systematically study the quality of 4,066 ChatGPT-generated code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal o…
On the Reliability and Explainability of Language Models for Program Generation
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu +1
Recent studies have adopted pre-trained language models, such as CodeT5 and CodeGPT, for automated program generation tasks like code generation, repair, and translation. Numerous…
Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Yue Liu, Chakkrit Tantithamthavorn, Li Li +1
Machine learning (ML)-based Android malware detection has been one of the most popular research topics in the mobile security community. An increasing number of research studies ha…
Automatically Recommend Code Updates: Are We There Yet?
Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu +2
In recent years, large pre-trained Language Models of Code (CodeLMs) have shown promising results on various software engineering tasks. One such task is automatic code update reco…
Deep Learning for Android Malware Defenses: a Systematic Literature Review
Yue Liu, Chakkrit Tantithamthavorn, Li Li +1
Malicious applications (particularly those targeting the Android platform) pose a serious threat to developers and end-users. Numerous research efforts have been devoted to develop…
Online NEAT for Credit Evaluation -- a Dynamic Problem with Sequential Data
Yue Liu, Adam Ghandar, Georgios Theodoropoulos
In this paper, we describe application of Neuroevolution to a P2P lending problem in which a credit evaluation model is updated based on streaming data. We apply the algorithm Neur…