CDI-Type II: Exploiting Collective Human Knowledge to Understand and Evolve Complex Networked Systems

大型联网计算机系统是有史以来最复杂、最精密的工程系统之一。由于这种复杂性，我们现有的计算环境不可靠、不安全，而且难以使用。这种情况的一个有趣的方面是，人们在实践中遇到的大多数问题都不是新的——他们以前已经被别人看到并解决了。因此，开发能够自动分析这种丰富的知识来源的技术是推进我们对这类重要的工程工件的理解的关键步骤。研究工作的重点是开发技术，自动处理有关先前遇到的问题和解决方案的现有人类交互存储库，以隔离问题的潜在解决方案。然后，它将使用多个虚拟机来评估每个潜在的解决方案，然后使用此评估来自动选择候选方案。这种方法的预期好处有三个方面。首先，开发联合分析自然语言文档和正式结构化计算机信息的方法可以导致对这些重要现象的新见解和更深入的理解。其次，这项研究将产生一类新的技术，通过利用用户群体的集体知识，在存在不确定性的情况下对计算机系统进行推理。最后，通过自动找到系统问题的解决方案，这些方法有望大幅降低使用计算机执行我们社会中许多关键活动的成本和风险。

Large networked computer systems are some of the most complex and sophisticated engineered systems ever constructed. Because of this complexity, our existing computing environment is unreliable, insecure, and difficult to use. One intriguing aspect of this situation is that most problems people encounter in practice are not new --- they have previously been seen and solved by others. Developing techniques that enable the automated analysis of this rich knowledge source is therefore a key step in advancing our understanding of this important class of engineered artifacts. The research effort focuses on developing techniques that automatically process existing repositories of human interactions regarding previously encountered problems and solutions to isolate potential solutions to the problem. It will then use multiple virtual machines to evaluate each of the potential solutions, then use this evaluation to automatically select an candidate.The expected benefits of this approach are three fold. First, developing methods that jointly analyze documents in natural language and formally structured computer information can lead to new insights and a deeper understanding of these important phenomena. Second, this research will yield a new class of techniques for reasoning about computer systems in the presence of uncertainty by leveraging collective knowledge of a user community. Finally, by automatically finding solutions to system problems, these methods hold out the promise of substantially reducing the cost and risks associated with using computers to perform many of the key activities in our society.