7 papers
Evaluating Large Language Models for Line-Level Vulnerability Localization
Jian Zhang, Chong Wang, Anran Li +4
Recently, Automated Vulnerability Localization (AVL) has attracted growing attention, aiming to facilitate diagnosis by pinpointing the specific lines of code responsible for vulne…
Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization
Yihao Huang, Chong Wang, Xiaojun Jia +5
Universal goal hijacking is a kind of prompt injection attack that forces LLMs to return a target malicious response for arbitrary normal user prompts. The previous methods achieve…
LLMs Meet Library Evolution: Evaluating Deprecated API Usage in LLM-based Code Completion
Chong Wang, Kaifeng Huang, Jian Zhang +4
Large language models (LLMs), pre-trained or fine-tuned on large code corpora, have shown effectiveness in generating code completions. However, in LLM-based code completion, LLMs…
A Prompt Learning Framework for Source Code Summarization
Tingting Xu, Yun Miao, Chunrong Fang +8
(Source) code summarization is the task of automatically generating natural language summaries (also called comments) for given code snippets. Recently, with the successful applica…
Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications
Wei Ma, Daoyuan Wu, Yuqiang Sun +5
Smart contracts are decentralized applications built atop blockchains like Ethereum. Recent research has shown that large language models (LLMs) have potential in auditing smart co…
TIGER: A Generating-Then-Ranking Framework for Practical Python Type Inference
Chong Wang, Jian Zhang, Yiling Lou +4
Python's dynamic typing system offers flexibility and expressiveness but can lead to type-related errors, prompting the need for automated type inference to enhance type hinting. W…