Large Language Model (LLM)-based agents are increasingly used for software engineering tasks, yet their performance is not determined by the base model alone. The agent harness substantially shapes how SE agents interact with repositories, execute actions, and validate solutions. However, the role of harness design rem...
Hai-Chuan Hu, Quan-Jun Zhang, Sheng-Cheng Yu et al.· 0 citations
Embedding an intelligent agent in an existing application creates a persistent coordination problem: users can revise goals and manipulate shared objects while delegated execution continues. We argue that dependable integration requires an explicit correspondence between task-level interaction and application behavior....
A large-scale empirical study based on an industrial dataset from Infineon, comprising 8,082 stakeholder requirements and 5,870 product requirements enriched with traceability links, decision outcomes, deviation rationales, and domain references, which provides concrete insight into industrial requirements intake and r...
Zixu Wang, Shengcheng Yu, Zhenchang Xing et al.· 0 citations
GUI agents have advanced rapidly, producing a growing body of frameworks, benchmarks, and applications. However, this growth has outpaced the maturity of the field. GUI agents remain technically brittle, incompletely engineered, and insufficiently validated for sustained real-world use. They are evolving into closed-lo...
Sheng-Cheng Yu, Yu-Chen Ling, Junyang Xing et al.· 1 citation
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