MAPE-K Formal Templates to Rigorously Design Behaviors for Self-Adaptive Systems

Author:

Iglesia Didac Gil De La1,Weyns Danny1

Affiliation:

1. Linnaeus University, Växjö, Sweden

Abstract

Designing software systems that have to deal with dynamic operating conditions, such as changing availability of resources and faults that are difficult to predict, is complex. A promising approach to handle such dynamics is self-adaptation that can be realized by a MAPE-K feedback loop (Monitor-Analyze-Plan-Execute plus Knowledge). To provide evidence that the system goals are satisfied, given the changing conditions, the state of the art advocates the use of formal methods. However, little research has been done on consolidating design knowledge of self-adaptive systems. To support designers, this paper contributes with a set of formally specified MAPE-K templates that encode design expertise for a family of self-adaptive systems. The templates comprise: (1) behavior specification templates for modeling the different components of a MAPE-K feedback loop (based on networks of timed automata), and (2) property specification templates that support verification of the correctness of the adaptation behaviors (based on timed computation tree logic). To demonstrate the reusability of the formal templates, we performed four case studies in which final-year Masters students used the templates to design different self-adaptive systems.

Publisher

Association for Computing Machinery (ACM)

Subject

Software,Computer Science (miscellaneous),Control and Systems Engineering

Cited by 109 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data fabric and digital twins: An integrated approach for data fusion design and evaluation of pervasive systems;Information Fusion;2024-03

2. Towards Feature-Based Analysis of the Machine Learning Development Lifecycle;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

3. A lightweight adaptive authentication protocol for power heterogeneous terminals;Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023);2023-10-20

4. Towards DevOps for Cyber-Physical Systems (CPSs): Resilient Self-Adaptive Software for Sustainable Human-Centric Smart CPS Facilitated by Digital Twins;Machines;2023-10-19

5. Human-Machine Teaming with small Unmanned Aerial Systems in a MAPE-K Environment;ACM Transactions on Autonomous and Adaptive Systems;2023-09-04

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3