36 citations · 107 across the 20 of their papers we have counts for
21 papers
Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation
Ivana Clairine Irsan, Ratnadira Widyasari, Huihui Huang +6
Static analysis remains a cornerstone of software security, yet the effectiveness of tools such as CodeQL is often limited by the substantial manual effort required to develop high…
PoCEvolve: Generating Proof-of-Concept Exploits from Security Patches with Vulnerability-Aware Prompt Evolution
Duc Manh Tran, Ratnadira Widyasari, Ivana Clairine Irsan +6
Ideally, the detailed information about a vulnerability should be made available together with the fixing commit. In practice, however, such details often become available only lon…
Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
Yue Liu, Ratnadira Widyasari, Yanjie Zhao +3
AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior s…
TitanCA: Lessons from Orchestrating LLM Agents to Discover 100+ CVEs
Ting Zhang, Yikun Li, Chengran Yang +15
Software vulnerabilities remain one of the most persistent threats to modern digital infrastructure. While static application security testing (SAST) tools have long served as the…
Revisiting Vulnerability Patch Identification on Data in the Wild
Ivana Clairine Irsan, Ratnadira Widyasari, Ting Zhang +7
Attacks can exploit zero-day or one-day vulnerabilities that are not publicly disclosed. To detect these vulnerabilities, security researchers monitor development activities in ope…
Back to the Basics: Rethinking Issue-Commit Linking with LLM-Assisted Retrieval
Huihui Huang, Ratnadira Widyasari, Ting Zhang +8
Issue-commit linking, which connects issues with commits that fix them, is crucial for software maintenance. Existing approaches have shown promise in automatically recovering thes…
Let the Trial Begin: A Mock-Court Approach to Vulnerability Detection using LLM-Based Agents
Ratnadira Widyasari, Martin Weyssow, Ivana Clairine Irsan +6
Detecting vulnerabilities in source code remains a critical yet challenging task, especially when benign and vulnerable functions share significant similarities. In this work, we i…
CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
Yikun Li, Ting Zhang, Ratnadira Widyasari +13
Accurate identification of software vulnerabilities is crucial for system integrity. Vulnerability datasets, often derived from the National Vulnerability Database (NVD) or directl…
JavaVFC: Java Vulnerability Fixing Commits from Open-source Software
Tan Bui, Yan Naing Tun, Yiran Cheng +3
We present a comprehensive dataset of Java vulnerability-fixing commits (VFCs) to advance research in Java vulnerability analysis. Our dataset, derived from thousands of open-sourc…
Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection
Xin Zhou, Duc-Manh Tran, Thanh Le-Cong +5
Software vulnerabilities pose significant security challenges and potential risks to society, necessitating extensive efforts in automated vulnerability detection. There are two po…
Evaluating Pre-trained Language Models for Repairing API Misuses
Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +3
API misuses often lead to software bugs, crashes, and vulnerabilities. While several API misuse detectors have been proposed, there are no automatic repair tools specifically desig…
Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models
Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +1
Software development involves collaborative interactions where stakeholders express opinions across various platforms. Recognizing the sentiments conveyed in these interactions is…
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…
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…
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…
Duplicate Bug Report Detection: How Far Are We?
Ting Zhang, DongGyun Han, Venkatesh Vinayakarao +5
Many Duplicate Bug Report Detection (DBRD) techniques have been proposed in the research literature. The industry uses some other techniques. Unfortunately, there is insufficient c…
Automatic Pull Request Title Generation
Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +3
Pull Requests (PRs) are a mechanism on modern collaborative coding platforms, such as GitHub. PRs allow developers to tell others that their code changes are available for merging…
AutoPRTitle: A Tool for Automatic Pull Request Title Generation
Ivana Clairine Irsan, Ting Zhang, Ferdian Thung +2
With the rise of the pull request mechanism in software development, the quality of pull requests has gained more attention. Prior works focus on improving the quality of pull requ…
iTiger: An Automatic Issue Title Generation Tool
Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +3
In both commercial and open-source software, bug reports or issues are used to track bugs or feature requests. However, the quality of issues can differ a lot. Prior research has f…