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le (1h8m54s)

Theoretical Foundations for Runtime Monitoring

Runtime monitoring/verification is a lightweight technique that complements other verification methods in a multi-pronged approach towards ensuring software correctness. The technique poses novel questions to software engineers: it is not easy to see which specifications are amenable to runtime monitoring, and it is not clear which monitors perform the required runtime analysis correctly. In this talk, I will present a theoretical framework that can be used to provide answers to those questions. I will view monitorability as a spectrum: the fewer monitor guarantees are required, the more properties become monitorable. I will then present a monitorability hierarchy ...
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le (1h4m32s)

CoNeCo: Concurrency, Networks and Coinduction

In recent years, concurrent Kleene algebra (CKA), an extension of Kleene Algebra (KA) that includes concurrent composition as a first-class citizen, has been proposed by Hoare et al. as a setting to study the algebraic properties of concurrent composition as an operator on programs.  Orthogonally, based on KA, Foster et al proposed NetKAT, a domain-specific language that can be used to program and verify policies of Software Defined Networks. in this talk, we will show how to develop a concurrent extension of NetKAT based on CKA, which supports expressing and verifying the concurrent filtering of packets — on the same ...
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le (1h10m48s)

The Legacy of Rudolph Kalman

In 1960 Rudolph Kalman published what is arguably the first paper to develop a systematic, principled approach to the use of data to improve the predictive capability of mathematical models. As our ability to gather data grows at an enormous rate, the importance of this work continues to grow too. The lecture will describe this paper, and developments that have stemmed from it, revolutionizing fields such space-craft navigation, weather prediction, oceanography and oil recovery; the lecture will also describe new application domains such as climate modeling, medical imaging and machine learning. Some mathematical details will be also provided, but limited to simple concepts such as optimization and iteration; the ...
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