Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...
We describe our efforts to use rule-based programming to produce a model of Jumbo, a run-time program generation (RTPG) system for Java. Jumbo incorporates RTPG following the simp...
The computational cost and precision of a shape style heap analysis is highly dependent on the way method calls are handled. This paper introduces a new approach to analyzing metho...
There are many different implementation approaches to realize the vision of feature oriented software development, ranging from simple preprocessors, over feature-oriented program...