Causal Message Sequence Charts

Scenario languages based on Message Sequence Charts (MSCs) and related notations have been widely studied in the last decade [14, 13, 2, 9, 5, 12, 8]. The high expressive power of scenarios renders many basic problems concerning these languages undecidable. The most expressive class for which several problems are known to be decidable is one which possesses a behavioral property called “existentially bounded”. However, scenarios outside that class are frequently exhibited by asynchronous distributed systems such as sliding window protocols. We propose here an extension of MSCs called causal Message Sequence Charts that preserves decidability without requiring existential bounds. Interestingly, it can also model scenarios from sliding window protocols. We establish the expressive power and complexity of decision procedures for various subclasses of causal Message Sequence Charts.