工业中的自我适应:一项调查

IF 2.2 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ACM Transactions on Autonomous and Adaptive Systems Pub Date : 2022-11-06 DOI:10.1145/3589227
Danny Weyns, I. Gerostathopoulos, Nadeem Abbas, J. Andersson, S. Biffl, Přemek Brada, T. Bures, A. D. Salle, M. Galster, Patricia Lago, G. Lewis, Marin Litoiu, Angelika Musil, Juergen Musil, Panos Patros, Patrizio Pelliccione
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引用次数: 3

摘要

计算系统构成了我们社会许多领域的支柱,从制造业到交通控制、医疗保健和金融系统。当软件在设计、构建和操作中起着至关重要的作用时,这些系统被称为软件密集型系统。自适应为软件密集型系统配备了一个反馈回路,可以自动执行需要人工操作人员执行的任务,也可以处理不确定的情况。这种反馈回路已经在各种实际应用中找到了出路;典型的例子是弹性云,以适应计算资源和自动化服务器管理,以快速响应业务需求。为了深入了解企业在实践中采用自适应的动机、采用自适应解决了哪些问题以及如何解决这些问题,以及企业采用自适应面临的困难和风险,我们进行了大规模的调查。我们收到了来自21个国家从业人员的184份有效回复。在对调查数据进行分析的基础上,以实证为基础对自适应的应用现状进行了概述。从中,我们获得了研究人员与行业需求检查其当前研究的见解,以及从业者在应用自适应方面比较其当前实践的见解。这些见解也为在实践中应用自我适应提供了机会,并为未来的行业研究合作铺平了道路。
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Self-Adaptation in Industry: A Survey
Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are referred to as software-intensive systems. Self-adaptation equips a software-intensive system with a feedback loop that either automates tasks that otherwise need to be performed by human operators or deals with uncertain conditions. Such feedback loops have found their way to a variety of practical applications; typical examples are an elastic cloud to adapt computing resources and automated server management to respond quickly to business needs. To gain insight into the motivations for applying self-adaptation in practice, the problems solved using self-adaptation and how these problems are solved, and the difficulties and risks that industry faces in adopting self-adaptation, we performed a large-scale survey. We received 184 valid responses from practitioners spread over 21 countries. Based on the analysis of the survey data, we provide an empirically grounded overview the of state of the practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation. These insights also provide opportunities for applying self-adaptation in practice and pave the way for future industry-research collaborations.
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来源期刊
ACM Transactions on Autonomous and Adaptive Systems
ACM Transactions on Autonomous and Adaptive Systems 工程技术-计算机:理论方法
CiteScore
4.80
自引率
7.40%
发文量
9
审稿时长
>12 weeks
期刊介绍: TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community -- and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community - and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. Contributions are expected to be based on sound and innovative theoretical models, algorithms, engineering and programming techniques, infrastructures and systems, or technological and application experiences.
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