163 citations · 493 across the 35 of their papers we have counts for
35 papers
Learning from the Test: Self-Referential Differential Testing for Deep RL Agents
Junda He, Jieke Shi, Zhou Yang +2
Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in real-world applications, ensurin…
Lossless Tensor Compression as Program Synthesis
Jieke Shi, Junda He, Wenjia Jiang +11
Model checkpoints are growing in both number and size, which makes archival, transfer, and deployment increasingly costly. General-purpose compressors can reduce storage requiremen…
Insecure Coding Preferences in Long-Term Memory: Security Risks for LLM-based Code Generation
Yuchen Chen, Wei Cheng, Yuan Xiao +7
LLM-based systems increasingly incorporate long-term memory to improve cross-session continuity. However, once insecure coding preferences are stored, they may silently influence s…
Neuro-Symbolic Reasoning for Vulnerability Detection
Yanjie Zhao, Hongjie Chen, Li Lu +3
Ask a large language model (LLM) whether a pointer dereference is safe, and it can often produce a plausible justification for ``yes''. The difficulty is that a fluent justificatio…
Curiosity-Driven Testing for Sequential Decision-Making Process
Junda He, Zhou Yang, Jieke Shi +5
Sequential decision-making processes (SDPs) are fundamental for complex real-world challenges, such as autonomous driving, robotic control, and traffic management. While recent adv…
Finding Safety Violations of AI-Enabled Control Systems through the Lens of Synthesized Proxy Programs
Jieke Shi, Zhou Yang, Junda He +4
Given the increasing adoption of modern AI-enabled control systems, ensuring their safety and reliability has become a critical task in software testing. One prevalent approach to…
PTM4Tag+: Tag Recommendation of Stack Overflow Posts with Pre-trained Models
Junda He, Bowen Xu, Zhou Yang +5
Stack Overflow is one of the most influential Software Question & Answer (SQA) websites, hosting millions of programming-related questions and answers. Tags play a critical role in…
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models
Zhou Yang, Zhipeng Zhao, Chenyu Wang +4
Given large-scale source code datasets available in open-source projects and advanced large language models, recent code models have been proposed to address a series of critical s…
CCBERT: Self-Supervised Code Change Representation Learning
Xin Zhou, Bowen Xu, DongGyun Han +3
Numerous code changes are made by developers in their daily work, and a superior representation of code changes is desired for effective code change analysis. Recently, Hoang et al…
Greening Large Language Models of Code
Jieke Shi, Zhou Yang, Hong Jin Kang +3
Large language models of code have shown remarkable effectiveness across various software engineering tasks. Despite the availability of many cloud services built upon these powerf…
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…
Unveiling Memorization in Code Models
Zhou Yang, Zhipeng Zhao, Chenyu Wang +4
The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse software engineering…
Source Code Data Augmentation for Deep Learning: A Survey
Terry Yue Zhuo, Zhou Yang, Zhensu Sun +5
The increasingly popular adoption of deep learning models in many critical source code tasks motivates the development of data augmentation (DA) techniques to enhance training data…
Synthesizing Speech Test Cases with Text-to-Speech? An Empirical Study on the False Alarms in Automated Speech Recognition Testing
Julia Kaiwen Lau, Kelvin Kai Wen Kong, Julian Hao Yong +7
Recent studies have proposed the use of Text-To-Speech (TTS) systems to automatically synthesise speech test cases on a scale and uncover a large number of failures in ASR systems.…
APISENS- Sentiment Scoring Tool for APIs with Crowd-Knowledge
Kisub Kim, Ferdian Thung, Ting Zhang +4
Utilizing pre-existing software artifacts, such as libraries and Application Programming Interfaces (APIs), is crucial for software development efficiency. However, the abundance o…
APIHarvest: Harvesting API Information from Various Online Sources
Ferdian Thung, Kisub Kim, Ting Zhang +4
Using APIs to develop software applications is the norm. APIs help developers to build applications faster as they do not need to reinvent the wheel. It is therefore important for…
What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issues
Zhou Yang, Chenyu Wang, Jieke Shi +5
Artificial Intelligence systems, which benefit from the availability of large-scale datasets and increasing computational power, have become effective solutions to various critical…
NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python
Ratnadira Widyasari, Zhou Yang, Ferdian Thung +8
Machine learning (ML) has gained much attention and been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as…
Representation Learning for Stack Overflow Posts: How Far are We?
Junda He, Zhou Xin, Bowen Xu +6
The tremendous success of Stack Overflow has accumulated an extensive corpus of software engineering knowledge, thus motivating researchers to propose various solutions for analyzi…
ASDF: A Differential Testing Framework for Automatic Speech Recognition Systems
Daniel Hao Xian Yuen, Andrew Yong Chen Pang, Zhou Yang +3
Recent years have witnessed wider adoption of Automated Speech Recognition (ASR) techniques in various domains. Consequently, evaluating and enhancing the quality of ASR systems is…
Prioritizing Speech Test Cases
Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi +4
With the wide adoption of automated speech recognition (ASR) systems, it is increasingly important to test and improve ASR systems. However, collecting and executing speech test ca…
Stealthy Backdoor Attack for Code Models
Zhou Yang, Bowen Xu, Jie M. Zhang +4
Code models, such as CodeBERT and CodeT5, offer general-purpose representations of code and play a vital role in supporting downstream automated software engineering tasks. Most re…
BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets
Chen Gong, Zhou Yang, Yunpeng Bai +8
Reinforcement learning (RL) makes an agent learn from trial-and-error experiences gathered during the interaction with the environment. Recently, offline RL has become a popular RL…
Answer Summarization for Technical Queries: Benchmark and New Approach
Yang Chengran, Bowen Xu, Ferdian Thung +8
Prior studies have demonstrated that approaches to generate an answer summary for a given technical query in Software Question and Answer (SQA) sites are desired. We find that exis…