{"title":"Software Self-adaptation and Industry: Blame MAPE-K","authors":"R. Lemos","doi":"10.1109/SEAMS59076.2023.00021","DOIUrl":null,"url":null,"abstract":"If software self-adaptation has to be widely adopted by industry, we need to think big, embrace complexity, provide easily deployed and cost-effective solutions, and justify trust. On fairness, MAPE-K should not solely take the blame. MAPE-K is one of the many interpretations of feedback loops apply to systems for which mathematical models - mostly based on control theory, are difficult to be synthesised. MAPE-K has provided a basic and widely accepted framework for justifying the deployment of feedback loops in software systems. Undoubtedly, it has helped to promote and advance the whole area, but now more concrete and resilient solutions are necessary. This position paper argues that, first, industry has been adopting software self-adaptation, perhaps in a way that may not be recognised by the academic community, second, generic solutions are unfeasible since every software system brings its own challenges, and thirdly, the generic stages associated with a feedback loop, like MAPE-K, are insufficient to solve specific challenges.","PeriodicalId":262204,"journal":{"name":"2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEAMS59076.2023.00021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

If software self-adaptation has to be widely adopted by industry, we need to think big, embrace complexity, provide easily deployed and cost-effective solutions, and justify trust. On fairness, MAPE-K should not solely take the blame. MAPE-K is one of the many interpretations of feedback loops apply to systems for which mathematical models - mostly based on control theory, are difficult to be synthesised. MAPE-K has provided a basic and widely accepted framework for justifying the deployment of feedback loops in software systems. Undoubtedly, it has helped to promote and advance the whole area, but now more concrete and resilient solutions are necessary. This position paper argues that, first, industry has been adopting software self-adaptation, perhaps in a way that may not be recognised by the academic community, second, generic solutions are unfeasible since every software system brings its own challenges, and thirdly, the generic stages associated with a feedback loop, like MAPE-K, are insufficient to solve specific challenges.
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软件自适应与产业:归咎于MAPE-K
如果软件自适应必须被行业广泛采用,我们需要考虑得更长远,接受复杂性,提供易于部署和成本效益高的解决方案,并证明信任是正确的。就公平而言,MAPE-K不应该独自承担责任。MAPE-K是对反馈回路的众多解释之一,这些解释适用于数学模型(主要基于控制理论)难以合成的系统。MAPE-K为在软件系统中部署反馈循环提供了一个基本的、被广泛接受的框架。毫无疑问,它有助于促进和推进整个地区,但现在需要更具体和有弹性的解决方案。本文认为,首先,工业界一直在采用软件自适应,也许以一种可能不被学术界认可的方式,其次,通用解决方案是不可行的,因为每个软件系统都有自己的挑战,第三,与反馈循环相关的通用阶段,如MAPE-K,不足以解决特定的挑战。
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