A primary goal of AOSD in the context of systems software has been to permit improved modularity without significantly degrading performance. Optimizations represent important cr...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
An optimization method is introduced for generating minimum-length test sequences taking into account timing constraints for FSM models of communication protocols. Due to active t...
In this paper, we discuss several facets of optimization in cloud computing, the corresponding challenges and propose an architecture for addressing those challenges. We consider ...
Marin Litoiu, C. Murray Woodside, Johnny Wong, Joa...