This paper concerns the use of static analysis for debugging purposes of declarative object-oriented equation-based modeling languages. We propose a framework where over- and unde...
Cache prediction for preemptive scheduling is an open issue despite its practical importance. First analysis approaches use simplified models for cache behavior or they assume si...
Weather and climate prediction software has enjoyed the benefits of exponentially increasing processor power for almost 50 years. Even with the advent of large-scale parallelism ...
We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...