163 citations · 634 across the 44 of their papers we have counts for
23 papers · 1 filter
Are We Ready to Embrace Generative AI for Software Q&A?
Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong +8
Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Ov…
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…
Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
Martin Weyssow, Xin Zhou, Kisub Kim +2
Large language models (LLMs) demonstrate impressive capabilities to generate accurate code snippets given natural language intents in a zero-shot manner, i.e., without the need for…
CUPID: Leveraging ChatGPT for More Accurate Duplicate Bug Report Detection
Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +1
Duplicate bug report detection (DBRD) is a long-standing challenge in both academia and industry. Over the past decades, researchers have proposed various approaches to detect dupl…
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…
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…
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.…
On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code
Martin Weyssow, Xin Zhou, Kisub Kim +2
Pre-trained language models (PLMs) have become a prevalent technique in deep learning for code, utilizing a two-stage pre-training and fine-tuning procedure to acquire general know…
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…
PICASO: Enhancing API Recommendations with Relevant Stack Overflow Posts
Ivana Clairine Irsan, Ting Zhang, Ferdian Thung +2
While having options could be liberating, too many options could lead to the sub-optimal solution being chosen. This is not an exception in the software engineering domain. Nowaday…
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…
Generation-based Code Review Automation: How Far Are We?
Xin Zhou, Kisub Kim, Bowen Xu +3
Code review is an effective software quality assurance activity; however, it is labor-intensive and time-consuming. Thus, a number of generation-based automatic code review (ACR) a…
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Bowen Xu +2
Although deep neural models substantially reduce the overhead of feature engineering, the features readily available in the inputs might significantly impact training cost and the…
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…
PatchZero: Zero-Shot Automatic Patch Correctness Assessment
Xin Zhou, Bowen Xu, Kisub Kim +5
Automated Program Repair (APR) techniques have shown more and more promising results in fixing real-world bugs. Despite the effectiveness, APR techniques still face an overfitting…
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…
CHRONOS: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports
Yunbo Lyu, Thanh Le-Cong, Hong Jin Kang +5
Tools that alert developers about library vulnerabilities depend on accurate, up-to-date vulnerability databases which are maintained by security researchers. These databases recor…
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…
Invalidator: Automated Patch Correctness Assessment via Semantic and Syntactic Reasoning
Thanh Le-Cong, Duc-Minh Luong, Xuan Bach D. Le +4
Automated program repair (APR) faces the challenge of test overfitting, where generated patches pass validation tests but fail to generalize. Existing methods for patch assessment…