Causal Message Sequence Charts

International audienceScenario languages based on Message Sequence Charts (MSCs) have been widely studied in the last decade. The high expressive power of MSCs renders many basic problems concerning these languages undecidable. However, several of these problems are decidable for languages that possess a behavioral property called ``existentially bounded''. Unfortunately, collections of scenarios outside this class are frequently exhibited by systems such as sliding window protocols. We propose here an extension of MSCs called causal Message Sequence Charts and a natural mechanism for defining languages of causal MSCs called causal HMSCs (CaHMSCs). These languages preserve decidable properties without requiring existential bounds. Further, they can model collections of scenarios generated by sliding window protocols. We establish here the basic theory of CaHMSCs as well as the expressive power and complexity of decision procedures for various subclasses of CaHMSCs. We also illustrate the modeling power of our formalism with the help of a realistic example based on the TCP sliding window feature