Prototype pollution is a critical class of taint-style vulnerabilities in JavaScript programs, enabling attackers to tamper with object prototypes and thereby alter program behavior in unexpected and often dangerous ways. Despite its severity, existing detection techniques struggle with excessive false positives and po...
De-Zhen Kong, Pei-Sen Yao, Jia-Kun Liu et al.· ACM Transactions on Software...· 0 citations
Real-world vulnerabilities often span multiple functions, yet most learning-based detectors classify each function in isolation: on a sample of real CVEs, we find that 71.7% of vulnerable functions require evidence from outside the function to be classified correctly. Agentic reinforcement learning (RL) could close thi...
Yikun Li, Ting Zhang, Jiakun Liu et al.· arXiv.org· 2 citations
DyRetriever is an efficient context retrieval method via partial dependency graphs that uses an LLM to first select a set of entry-point functions and then perform multi-hop reasoning along the code dependency graph, eliminating manually designed rules and enabling flexibility across scenarios.
Zhongxin Liu, Zhonghao Jiang, Zhi-Fan Ye et al.· 1 citation
Optimo is proposed, a multi-level LLM-based code optimization approach built on a novel Mixture-of-Prompts (MoP) architecture that achieves up to 57.48% opt%, and consistently outperforms the best baseline by up to 96.51% in terms of opt%.
Yun Peng, Jun Wan, Jiakun Liu et al.· arXiv.org· 0 citations
A high-quality benchmark of 1,000 code refinement instances from 328 Python, Java, and JavaScript repositories that focused on one of the most challenging code refinement scenarios that strictly requires repository-level knowledge reasoning, and a straightforward method, RepoRefiner, which retrieves repository-level co...
Ke Wang, Peng Lan, Jia-Kun Liu et al.· ACM Transactions on Software...· 1 citation
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