Model inference and testing of distributed systems

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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.