Model inference and testing of distributed systems

软件系统中最近的重要趋势，如大数据和复杂网站，是由于分布式系统的快速发展而成为可能。这些系统是全球数十亿人日常网络体验的一个组成部分。例如，所有大公司的后端服务都托管在数据中心，这些数据中心执行复杂的分布式系统，以提供可扩展、可靠和高度可用的服务。然而，分布式系统的开发人员仍然在努力实现和维护这些系统，因为很少有工具可以帮助他们理解系统的行为并测试其正确性。 我的建议的目的是推进在分布式系统的建模和调试的艺术状态。这项工作的成果将是一套开源软件工具，将帮助工程师更快地构建强大的分布式系统，并减少错误。这项工作将与工业界和学术界有关。它将解决日常软件工程师所面临的问题，并扩展我们对如何推理分布式系统的复杂执行以及如何诱导这些系统中的执行以探索和测试其行为的理解。 此外，这项研究将提供重要的和宝贵的培训，研究生和本科生。它将培养出具有分布式系统技能的高素质人才，这些技能受到加拿大所有主要软件公司的重视和积极追捧。

Recent important trends in software systems, such as big data and complex websites, are made possible by rapid advances in distributed systems. These systems are an integral part of the everyday web experience for billions of people worldwide. For example, the back-end services of all of the major companies are hosted in data-centers that execute complex distributed systems to provide scalable, reliable, and highly available services. However, developers of distributed systems continue to struggle in implementing and maintaining these systems as there are few tools that can help them understand a system's behaviors and test its correctness. The objective of my proposal is to advance the state of the art in modeling and debugging of distributed systems. The outcome of this work will be a set of open source software tools that will help engineers to build robust distributed systems quicker and with fewer mistakes. This work will be relevant to both industry and academics. It will solve problems faced by everyday software engineers as well as extend our understanding of how to reason about complex executions of distributed systems and how to induce executions in these systems to explore and test their behaviors. Further, this research will provide important and invaluable training to both graduate and undergraduate students. It will produce highly-qualified personnel with a distributed systems skill-set that is prized and actively sought after by all the major software companies in Canada.