SGER: Applying Digital Evolution to Behavioral Models

SGER：将数字进化应用于行为模型

• 批准号: 0750787
• 负责人: Betty Cheng
• 金额: --
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0750787&HistoricalAwards=false
• 关键词: SGER; Applying; Digital; Evolution; Behavioral

ABSTRACT0750787ChengMichigan StateThe Problem. Computing technology now affects nearly every dimension of modern society: managingcritical infrastructure such as power grids and telecommunication networks; supporting electronic commerceand medical information systems; and controlling the operation of aircraft and automobiles. This pervasiveness of computing technology, coupled with its rapidly increasing complexity, gives rise to the need for computer systems that are able to adapt to changing conditions. In the last decade, extensive research has been conducted on many aspects of self-adaptive software systems. Examples include adaptive software mechanisms [1 20]; software-architecture-based techniques for supporting dynamic adaptation [21 38]; adaptable and extensible operating systems [39 42]; and requirements-level and formal methods-based techniques [43 52]. This research has greatly improved our understanding of adaptive software and several key supporting concepts, including computational reflection [53 55], separation of concerns [12, 56], component-based design [57, 58], and transparent interception of program flow [59 61].Despite these advances, designing an adaptive software system remains a very challenging task. We speculatethat much of the difficulty is due to the fact that adaptive software is being designed and implemented usingtraditional tools and environments intended for the development of non-adaptive software. We contend that thefull potential of dynamically adaptive software systems cannot be realized without fundamental advances inthe corresponding development environments. Such environments must enable developers to explicitly addressthose aspects of the design problem that distinguish adaptive systems from non-adaptive systems. These issuesinclude anticipating how the software may need to adapt in the future, constructing decision-making softwareto govern the adaptation, and ensuring that system integrity is not compromised by adaptation.

摘要0750787密歇根州的问题。计算技术现在几乎影响到现代社会的各个方面：管理关键基础设施，如电网和电信网络;支持电子商务和医疗信息系统;控制飞机和汽车的运行。计算技术的这种普遍性，加上其快速增加的复杂性，产生了对能够适应变化的条件的计算机系统的需求。在过去的十年中，人们对自适应软件系统的许多方面进行了广泛的研究。例子包括自适应软件机制[1 20];支持动态适应的基于软件架构的技术[21 38];可适应和可扩展的操作系统[39 42];以及基于需求级和形式化方法的技术[43 52]。这项研究极大地提高了我们对自适应软件和几个关键支持概念的理解，包括计算反射[53 55]，关注点分离[12，56]，基于组件的设计[57，58]和程序流的透明拦截[59 61]。尽管有这些进步，设计自适应软件系统仍然是一项非常具有挑战性的任务。我们推测，很大程度上的困难是由于这样一个事实，即自适应软件的设计和实施使用传统的工具和环境，旨在为非自适应软件的发展。我们认为，动态自适应软件系统的全部潜力，不能实现相应的开发环境没有根本的进步。这样的环境必须使开发人员能够明确地解决设计问题的那些方面，区分自适应系统和非自适应系统。这些问题包括预测软件在未来可能需要如何适应，构建决策软件来管理适应，并确保系统的完整性不受适应的影响。