Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
We present a technique that improves random test generation by incorporating feedback obtained from executing test inputs as they are created. Our technique builds inputs incremen...
Carlos Pacheco, Shuvendu K. Lahiri, Michael D. Ern...
We explore the problem of modeling Internet connectivity at the Autonomous System (AS) level and present an economically-principled dynamic model that reproduces key features of t...
Jacomo Corbo, Shaili Jain, Michael Mitzenmacher, D...
Constructing correct distributed systems from their high-level models has always been a challenge and often subject to serious errors because of their non-deterministic and non-at...
Borzoo Bonakdarpour, Marius Bozga, Mohamad Jaber, ...
d by recent research in abstract model checking, we present a new approach to inferring dependent types. Unlike many of the existing approaches, our approach does not rely on prog...