Data Representation and Efficient Solution: A Decision Diagram Approach

Decision diagrams are a family of data structures that can compactly encode many functions on discrete structured domains, that is, domains that are the cross-product of finite sets. We present some important classes of decision diagrams and show how they can be effectively employed to derive “symbolic” algorithms for the analysis of large discrete-state models. In particular, we discuss both explicit and symbolic algorithms for state-space generation, CTL model-checking, and continuous-time Markov chain solution. We conclude with some suggestions for future research directions.