Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
We introduce a new kernel language for modeling hardware/software systems, adopting multiple heterogenous models of computation. The language has formal operational semantics, and...
Our paper aims at proposing a framework that allows programmers to exploit the benefits of exception handling throughout the entire development Java programs by modeling exception ...
Today, object-oriented requirements specifications typically combine a scenario (or use case) model and a class model for expressing functional requirements. With any such combina...