S. Stevanetic, Konstantinos Plakidas, Tudor B. Ionescu, D. Schall, Uwe Zdun
{"title":"Supporting quality-driven architectural design decisions in software ecosystems","authors":"S. Stevanetic, Konstantinos Plakidas, Tudor B. Ionescu, D. Schall, Uwe Zdun","doi":"10.1145/2993412.3003383","DOIUrl":null,"url":null,"abstract":"System quality attributes (QAs) are often considered as the most important decision drivers. In this paper, motivated by the decision making in a smart-city software ecosystem, we extend our previous approach that integrates reusable architectural design decisions (ADDs) with the QAs, by integrating tactics that support quality-driven decision making. In addition, we present an approach that enables system evolution, based on controlled and adaptable decision making and utilizing real data obtained during system monitoring. The approach integrates the previous approach that uses tactics with the existing model-driven development paradigm and the corresponding tools.","PeriodicalId":409631,"journal":{"name":"Proccedings of the 10th European Conference on Software Architecture Workshops","volume":"1 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proccedings of the 10th European Conference on Software Architecture Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2993412.3003383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
System quality attributes (QAs) are often considered as the most important decision drivers. In this paper, motivated by the decision making in a smart-city software ecosystem, we extend our previous approach that integrates reusable architectural design decisions (ADDs) with the QAs, by integrating tactics that support quality-driven decision making. In addition, we present an approach that enables system evolution, based on controlled and adaptable decision making and utilizing real data obtained during system monitoring. The approach integrates the previous approach that uses tactics with the existing model-driven development paradigm and the corresponding tools.