Agent-Integrated Software (AIS) embeds an intelligent agent in a conventional application, supporting both human operations and agent actions. Human operations let users make precise changes and inspect results, while agent actions carry out routine or multi-step tasks. These complementary roles make coexistence a like...
Ding Yang, Yu-Chen Ling, Sheng-Cheng Yu et al.· 0 citations
A systematic empirical study of harness effects in SE agents shows that harness effectiveness depends jointly on model capability and task type, and highlights harness design as a first-class factor in SE-agent performance and provides insights for building more effective and efficient coding agents.
Hai-Chuan Hu, Quan-Jun Zhang, Sheng-Cheng Yu et al.· 2 citations
CacheReforge, which represents stale KV caches as layerwise mixed-version objects, combines per-layer adapter anchors, calibrated sensitivity, accumulated drift, and executable restart boundaries to select direct reuse, bounded recomputation, or complete affected-suffix recovery.
Yu-Hang Cao, Yan-Zhou Mu, Chun-Rong Fang et al.· 0 citations
This paper introduces Agent-Integrated Software (AIS) as a software pattern combining a conventional core, direct interaction, and a built-in agent, and Intent-Level Interaction Abstraction (IIA) as the task semantics through which users inspect and control delegated work.
Sheng-Cheng Yu, C. Fang, Zhen-Yu Chen· 2 citations
The results show that reliable malicious-Skill detection requires both broader cross-source benchmark coverage and evaluation that jointly measures attack detection and benign over-flagging.
BASM is proposed, which augments each skill with explicit boundary fields, which transforms each retrieved skill from an unconditional action template into state-conditioned guidance: the agent applies the skill when its conditions hold, suppresses inapplicable tool calls when they do not, and issues targeted repairs w...
Zi-Han Lin, Zhen-Yu Chen, Jiawen Wei et al.· 1 citation
This paper proposes ARIA, an automated red-teaming framework for crafting covert and effective backdoored instructions against customized LLMs, which significantly outperforms existing attacks in evading platform-side and user-side detection, and stays effective against existing defense methods.
Yuchen Chen, Wei Cheng, Yuan Xiao et al.· Proceedings of the 41st IEEE...· 0 citations
ReProAgent is a multi-stage agent framework for reproduction test generation from issue reports that decomposes the task into four agent stages: bug localization, root cause analysis, test planning, and test generation, and generalizes across multiple backbone LLMs.
Quanjun Zhang, Yi Zheng, Ye Shang et al.· 1 citation
TestAgent is proposed, an LLM-based test generation approach that addresses the above limitations by emulating human testing practices via a multi-agent collaboration mechanism and equips TestAgent with a set of tool APIs that can be invoked dynamically in an on-demand and adaptive manner.
Quanjun Zhang, Ye Shang, Siqi Gu et al.· arXiv.org· 0 citations
TestAgent, a multi-agent tool implemented as a VS Code extension that automates the generation of high-quality unit tests for Java projects using repository-level Code Knowledge Graphs, demonstrates its practical utility for regression testing and bug discovery.
Ye Shang, Quanjun Zhang, Zheng Zhan et al.· SIGSOFT FSE Companion· 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
This survey aims to clarify the conceptual boundaries of self-evolving coding agents and provide a foundation for designing more adaptive, reliable, and software-aware agentic systems.
Hao Zhou, Hai-Chuan Hu, Tianyu Luo et al.· 0 citations
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