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Answer Is Cheap, Show Me the Evidence! Augmenting Automated Vulnerability Assessment with Evidence
Shengyi Pan, Zelong Zheng, Jiayuan Zhou +3
Software vulnerability (SV) assessment helps prioritize remediation by characterizing reported vulnerabilities. Existing automated methods predict assessment results from SV report…
SmellCC: A Tool for Automated Code Smells Remediation
Xiaoting Zhang, Yujie Zhang, Zhipeng Gao +2
Code smells significantly threaten software maintainability by accumulating technical debt, yet developers often lack the resources to manually address these flaws under tight rele…
Automating Just-In-Time Python Type Annotation Updating
Zhipeng Xue, Zhipeng Gao, Xing Hu +3
Type annotations are more and more popular in Python projects to avoid type errors caused by Python's dynamic typing feature. However, when developers change source code, these typ…
Refploit: Facilitating Exploit Construction via Code-Agent Trajectory Repair
Zirui Chen, Zhipeng Xue, Jiayuan Zhou +3
Vulnerability exploits play a crucial role in assessing the downstream impact of Java library vulnerabilities. While some vulnerabilities are accompanied by disclosed exploit refer…
ATTAIN: Automated Exploit Failure Analysis through Trace-Driven Diff Analysis
Xinwei Mao, Zirui Chen, Xing Hu +1
Exploits are widely used to check whether library vulnerabilities appear in different versions and to mark affected version ranges. Exploit-based checks sometimes fail because expl…
On the Shoulders of Giants: Empowering Automated Smart Contract Auditing via the GiAnt Corpus
Xiaoting Zhang, Zhipeng Gao, Yiran Lv +3
High-quality smart contract auditing datasets are crucial for evaluating security tools and advancing smart contract security research. Two major limitations of existing datasets a…
Triggering and Detecting Exploitable Library Vulnerability from the Client by Directed Greybox Fuzzing
Yukai Zhao, Menghan Wu, Xing Hu +3
Developers utilize third-party libraries to improve productivity, which also introduces potential security risks. Existing approaches generate tests for public functions to trigger…
An Empirical Study of Speculative Decoding on Software Engineering Tasks
Yijia Li, Junkai Chen, Xing Hu +1
Large Language Models (LLMs) have become widely used for Software Engineering (SE) tasks, spanning from function-level code generation to complex repository-level workflows. Howeve…
Verify Implementation Equivalence of Large Models
Qi Zhan, Xing Hu, Xin Xia +1
Verifying whether two implementations of the same large model are equivalent across frameworks is difficult in practice. Even when they realize the same computation, their graphs m…