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David Lo

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Open access Oct 2026

E2WR: An Effective and Efficient Reduction Framework for WebAssembly Binaries

WebAssembly (Wasm) is a prominent programming language enabling high-performance execution across diverse computing environments. However, bugs in Wasm runtimes, which execute Wasm binaries, can lead to severe security breaches and system failures. Manually debugging Wasm binaries that trigger such runtime bugs is exce...

Shi-Yao Zhou, Ning-Yu He, David Lo et al. · 0 citations
#reinforcement learning Open access Oct 2026

From Greedy Steps to Global Optimization: Learning Sequential Test Suite Generation

With the rapid evolution of Large Language Models (LLMs), automated software testing is witnessing a paradigm shift. While proprietary models like GPT-4o demonstrate impressive capabilities, their high deployment costs and data privacy concerns make open-source LLMs the practical imperative for many academic and indust...

Guo-Qing Wang, Cheng-Ran Yang, Xiao-Xuan Zhou et al. · 0 citations
Jul 2026

Multi-level Code Optimization via Mixture of Prompts

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. · 0 citations
Jul 2026

Evaluating Incompatible Third-party Library API Usage in LLM-based Code Completion

An automated framework that builds a versioned TPL API Knowledge Base and a large-scale benchmark that proposes two lightweight solutions, Real-time Detection and Lightweight Repair, to mitigate ITAUs and provide a foundation for more compatibility-aware code generation in evolving software ecosystems.

Li Lin, Yaorui Fei, Yunfeng Shen et al. · 0 citations
Review Aug 2026

Code Refinement with Repository Context: How Far are We?

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. · 1 citation

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