{"title":"A Paradigm Shift in Service Research: The Case of Service Composition","authors":"Marco Aiello","doi":"10.1109/TSC.2025.3552345","DOIUrl":null,"url":null,"abstract":"Recent advancements in artificial intelligence, particularly in machine learning and neural networks, have significantly influenced various domains, including service computing. Large Language Models (LLMs) are at the forefront of this transformation, introducing new paradigms for automation and decision-making. This paper examines the evolving impact of LLMs on service composition, a fundamental problem in service computing. By analyzing shifts in research approaches, methodologies, and system architectures, we highlight how LLM-driven automation challenges traditional composition techniques. The discussion provides insights into emerging opportunities, limitations, and research directions, emphasizing the need to rethink service composition in the era of AI-driven automation.","PeriodicalId":13255,"journal":{"name":"IEEE Transactions on Services Computing","volume":"18 3","pages":"1213-1215"},"PeriodicalIF":5.8000,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Services Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10930728/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Recent advancements in artificial intelligence, particularly in machine learning and neural networks, have significantly influenced various domains, including service computing. Large Language Models (LLMs) are at the forefront of this transformation, introducing new paradigms for automation and decision-making. This paper examines the evolving impact of LLMs on service composition, a fundamental problem in service computing. By analyzing shifts in research approaches, methodologies, and system architectures, we highlight how LLM-driven automation challenges traditional composition techniques. The discussion provides insights into emerging opportunities, limitations, and research directions, emphasizing the need to rethink service composition in the era of AI-driven automation.
期刊介绍：
IEEE Transactions on Services Computing encompasses the computing and software aspects of the science and technology of services innovation research and development. It places emphasis on algorithmic, mathematical, statistical, and computational methods central to services computing. Topics covered include Service Oriented Architecture, Web Services, Business Process Integration, Solution Performance Management, and Services Operations and Management. The transactions address mathematical foundations, security, privacy, agreement, contract, discovery, negotiation, collaboration, and quality of service for web services. It also covers areas like composite web service creation, business and scientific applications, standards, utility models, business process modeling, integration, collaboration, and more in the realm of Services Computing.
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