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程密歇根州问题。计算技术现在几乎影响着现代社会的方方面面：管理电网和电信网络等关键基础设施；支持电子商务和医疗信息系统；并控制飞机和汽车的运行。计算技术的普及，加上其迅速增加的复杂性，引发了对能够适应不断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]；适应性强且可扩展的操作系统[39 42]；以及需求级和基于正式方法的技术[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]。尽管取得了这些进步，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，大部分困难是由于自适应软件是使用用于开发非自适应软件的传统工具和环境来设计和实现的。我们认为，如果相应的开发环境没有根本性的进步，动态自适应软件系统的全部潜力就无法实现。这样的环境必须使开发人员能够明确解决设计问题中区分自适应系统和非自适应系统的那些方面。这些问题包括预测软件将来可能需要如何适应，构建决策软件来管理适应，以及确保系统完整性不会因适应而受到损害。