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Computer Science > Software Engineering

arXiv:2509.24380 (cs)
[Submitted on 29 Sep 2025 (v1), last revised 4 Jul 2026 (this version, v3)]

Title:Agentic Services Computing

Authors:Shuiguang Deng, Hailiang Zhao, Ziqi Wang, Wenzhuo Qian, Xiang Ao, Guanjie Cheng, Jianwei Yin, Albert Y. Zomaya, Schahram Dustdar
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Abstract:Services computing has evolved from Web services and microservices to cloud-native and serverless paradigms. These approaches established mature principles for describing, composing, deploying, operating, and governing reusable software functions. LLM-based agents now introduce a fundamentally different service form. Service value in this paradigm emerges not only from invoking predefined functions but also from delegating goals to autonomous entities. These entities understand context, use tools, collaborate with peers, and act across open environments. This shift raises a core question for services computing. How can goal-driven, stateful, tool-mediated, and accountable autonomous behavior be engineered and managed as a service? Recent studies on LLM agents and multi-agent systems provide important foundations. A clear service-centered research roadmap for this emerging paradigm nevertheless remains absent. This work introduces Agentic Services Computing (ASC) to address this gap. ASC extends services computing from managing reusable functional endpoints to engineering and governing autonomous service entities. It defines agentic services as service-oriented autonomous agents. Related research is organized through a lifecycle view that connects service objects, system structures, enabling infrastructure, evaluation metrics, application evidence, and open challenges. This service-centered perspective establishes a foundation for future service ecosystems. Autonomous agents can thus be systematically described, composed, delivered, monitored, audited, and evolved as first-class services.
Subjects: Software Engineering (cs.SE)
Cite as: arXiv:2509.24380 [cs.SE]
  (or arXiv:2509.24380v3 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2509.24380
arXiv-issued DOI via DataCite

Submission history

From: Hailiang Zhao [view email]
[v1] Mon, 29 Sep 2025 07:29:18 UTC (673 KB)
[v2] Fri, 10 Oct 2025 05:32:09 UTC (596 KB)
[v3] Sat, 4 Jul 2026 03:50:21 UTC (2,549 KB)
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